prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What is the research opportunity that is mentioned?

Read the following text and answer briefly.

Context 1: My Aspergers Child: COMMENTS & QUESTIONS [for Feb , 2017]
I emailed you a while back and you mentioned that I could email when I needed to  Thank you  I last wrote you in December that my son became involved in a dispute involving the local police  We have had 3 court dates  It keeps delaying due to not being able to come to an agreement  But the attorney, even though he was just vaguely familiar with Aspergers, has been very good with Craig  He has the compassion and excellence that is needed here  What started out very bad is turning into a good thing  It will probably take another 90 days or more 
But Craig is working hard  Too hard sometimes  He goes to therapy 3 times a week  Doing excellent  He's more focused and can calm down easier  He's got a lot on his plate but has support from his family  From his attorney  From therapy  And from his work 
He has been renting a room from a lady who has a son with ADHD  It is good for him  I'm a little worried though because since she smokes he wants to find his own place  With all the costs he has to balance it out financially  That is good  I can't help him more than I am which is good  He is stepping up and taking responsibility  He is listening much better 
He is going to have an evaluation today to get an accurate diagnosis  I understand that is a little difficult since he is an adult  Also the PTSD may cover it over  The attorney stated it would help to have the diagnosis 
Aware this is a long update, but thanks for reading  I am fighting much guilt still but I have a lot of peace now  My daughter and her 4 year old son also have Aspergers symptoms  So my life chapters may not close for a while  :-)
My name is Mac  I'm sure you're quite busy, so I'll get right to it I just wanted to pass on compliments on My Aspergers Child and your post, How to Implement the GFCF Diet: Tips for Parents of Autistic Children 
Me and my wife absolutely loved it!
I got a facebook message from him today begging to be able to come home saying he misses home and he will change  He says he will follow rules now  I stated to him the simple rules he has to follow which were - No weed in my house, or smoked in my house, coming home at curfew, going to school, no skipping, no drugs at school, and to drop the attitude of I am 17 I can do whatever I want 
I have made it very clear that if I see any drugs in my home I will be calling the police, as well as if I see signs of it being sold by him I will report him  (He has never had selling amounts in my house,     I believe it's being kept at his "friends" which of course I have no proof of    I just know it is not here 
I know my battle is not over by a long shot, I am sure we will have more consequences and possibly another being kicked out, but I am going to think positive and hope that he learned some form of a valuable lesson here 
Thank you so much for the guidance, never in a million years did I ever think I'd be on this side, (the one needing the help, as I am the one who helps )
I am going to go back to the start of the program like I said earlier and keep notes close by for reference 
Thanks for all you do, helping us all with ODD children/teens
I have a small company providing educational support services to a few families who have children with various disabilities in Ohio  One of the families has multiple adopted children of whom several have significant attachment disorders including RAD  As an experienced teacher and foster parent I have some experience in working with children who have extensive trauma backgrounds  However, I could use additional training  Also working with these children are two staff members with minimal background in attachment disorders who would also benefit from training primarily in behavior management  The primary caregiver to the children does a wonderful job managing their needs  In order to further develop team cohesion, I'm hoping to include her in any training as well 
Is it possible to schedule such a training session with you? If so, please let us know what will work for you including time, place, and cost  Thank you for your assistance 
I just listed to your tapes on dealing with an out of control, defiant teen  I'd like to ask your advice on a particular situation we have  Our 15 year old daughter is smoking pot almost every day at school  Because we had no way to control the situation, we told her, fine, go ahead and smoke weed  However, you will no longer receive the same support from us  You will not have your phone, lunch money to go off campus (she has an account at the school for the cafeteria she can use), and you will be grounded until you can pass a drug test  We will not be testing you except for when you tell us you are ready to be tested  She is now saying she's suicidal because she feels so isolated, yet she continues to smoke weed  In fact, she tried to sneak out last night but was foiled by our alarm system  For the particular drug test we have, I read it takes about 10 days of not smoking to pass the test  What would you do? Please advise 
I am having a problem with my 18 year old son, Danny, with high functioning autism  We finally had him diagnosed when he was 16 years old  I always knew something was going on with him but the doctors misdiagnosed him as bipolar  It's been 2 years now and he will not accept his diagnosis  He won't talk about it and when I try to bring it up he gets very angry  I've tried telling him that it's not a bad thing, that there's been many, many very successful people with Aspergers  He won't tell anyone and refuses to learn about managing life with it  He once shared with me that the other kids at school use it as an insult, like saying someone is so autistic when they do something they don't approve of  So he doesn't want anyone to know  He's turned down services that could help him  He has a girlfriend, going on 8 months  He won't tell her and they're having problems arguing a lot and I wonder if it would help for her to know 
I'm sad that he thinks it's a life sentence to something horrible instead of accepting, embracing it and learning about it more so he maybe can understand why he's struggling  I told him that he doesn't need to shout it out to the whole world but he won't even accept it himself 
I don't know how to help him with it and because he's almost 19 I have limited control now  It's made my life easier knowing what we're dealing with and I think his life would be easier is he accepted it 
Please help me help him 
I am a clinical psychologist in NYC who now has several (!!) children I see who have RAD  In 20 years of practice, I’d seen only one case  Now, I have at least three children with this  I have no training, per se, in working with this children though I know about setting structure, consistency, etc  I do a lot of work with parents about parenting  I work primarily within the school setting in a charter school whose mission is to educate children on the autism spectrum in a mainstream setting  We use Michelle Garcia Winner’s social thinking program with our ASD kids  I also work with gen ed kids in the school who are at-risk; the school is in the inner city from where the majority of our non-ASD kids live 
It would have been so much easier to mention to my adult son that I think (I know he does, but want to ease into the subject)
he has Asperger's when we were living together two years ago  He has since moved to Tennessee working in his field of interest
which is 3-D printing and software development  I am so happy for him that he has found his way into a job that he truly enjoys
even though he's socially isolated 
He's not diagnosed and does not know he has it  How I know is his classic symptoms being sensory issues (fabric feeling like sandpaper)
communication difficulties, meltdowns and much more  Throughout his childhood I just felt he was a bit different  Nothing major stood out and time
just passes, misdiagnosis of ADHD, low frustration, etc  We've talked about his ADHD numerous times (which I now know he doesn't have) 
It's so much easier to communicate with him now that I know he has Asperger's  I keep it "slow and low" in talking, with long moments
of silence and then we connect  It's really too bad that Asperger's got a diagnostic code back in the 90's, yet all the so called doctors,
physiologist's, etc, didn't know how to diagnose it  Too bad 
There seems to be no one answer to "should I tell my adult son he has Asperger's" from a few specialists I asked  He is typical Asperger,
complicated, highly intelligent (high IQ), anxiety at times, socially isolated, hard to make friends  Not knowing how he will react is the hard part 
How will he be better off knowing he has it? Do I wait to tell him in person, or ease into it with him over Skype? He likes direct, honest, concrete communication 
Why is this so hard for me? Maybe because no one know's if he is going to be better off knowing or not  Do you know if people are better off
knowing? I try to get up the courage to just let him know, then I back down 
I have been searching the web looking for advice and came upon your site  I am trying to read blogs, websites, books, and articles to help guide me  I was so happy when you said that I could ask you a question  My husband and I are struggling with my 27 year old son who lives with us 
Kyle is the youngest of 4 sons  He is a college graduate but never could find the "right" job  He has always been quiet and never had a lot of friends  Two years ago, his girlfriend broke up with him  Kyle had an online gambling addiction and was using pot all the time  After the breakup, Kyle was very depressed and started using heroin and finally told my husband he was using  He is now seeing a psychiatrist who has him on suboxone and antidepressants  He is also seeing a psychologist weekly for counseling but it does not seem to be helping 
Last October,, Kyle lost his job, got drunk, and was agitated and came home , fighting with us, damaging our home and being verbally abusive  My other son , age 32, who also lives with us called the police and Kyle got arrested  He is currently in the family court system  He went through an anger management course and now is in substance abuse classes  Kyle continues to verbally abusive to me and blame me for everything  He says he "hates me "and calls me terrible names  At times, he pushes my husband and intimidates me  My husband and I are so upset  We just hired an attorney for him because since he has been going to these classes, he is getting more depressed and not getting better  Kyle continues to drink while taking his meds prescribed by the psychiatrist and then he has his "moods " My husband and I have met once with the psychiatrist just to give him background information when Kyle started with him 
At this point, we do not know what to do  We never thought at this stage of our life, we would be supporting and spending our retirement money on adult children  I do not know why Kyle hates me, I could not have been a better mom  My husband and I have no life and just do not know what it the right path we should take  Kyle does not want anything to do with us  He spends all his time in his room playing football online We have tried tough love versus caring and love and understanding  Do you have any advice for me?
This whole ODD and ADHD is killing me as a parent  I work in the field of adult psych and addictions so I am well educated  I have been dealing with my teen being like this for almost 3 years and I totally lost my cool today with my 17-year-old son to the point I told him he is out of the house  He can never simple rules, comes and goes as he pleases sometimes doesn't come home, just recently back in school from several suspension for drug related    I am just so exhausted  He has made me hate life, hate being a parent and sometimes I just feel like not even being here  I bought your program in hopes to it would help, I am at week three and I feel things are getting worse    what am I doing wrong??
My partner hasn't been diagnosed yet but I know he has aspergers   day to day is a struggle   I feel I'm going crazy with how he makes me feel Feel let down constantly  He lies alot but I've been told they can't but I know he does I just feel trapped and unloved We have a 4yr old daughter together and my main worry with how he is that it will effect our daughter ; (his skills as a parent are so weak He can't disapline at all Feel so alone  he hides it well too I just wondered if things will get worse? He's angry so quick in arguments Scares me etc I can't leave as he's the main bread winner and our daughter loves him to bits Don't know why I'm writing this  Sorry if I'm going on and not making sense :(
I wanted to let you know about a research opportunity for children, teens, and young adults with autism  I am studying the effects of Brazilian Jiu Jitsu, and psychotherapy on helping people with autism develop subjective awareness of others 
I am writing you to see if this might help someone in your practice, or to see if you might know of someone with autism who may benefit from participating in this study  The requirements of the study will be:
1  A participant should be between 7-21 years of age and have a diagnosis of Autism Spectrum Disorder 
2  The participant should enroll in an approved Jiu Jitsu Academy and attend at least two sessions a week for a period of six months 
3  The participant should enroll in social skills groups, provided by my office or be in a steady psychotherapeutic relationship in your office, at least once a week, or minimally two to three times a month 
4  The participant will be given a SRS (Social Responsiveness Scale) test at the beginning of the study, at three months, and again at six months 
If you know of anyone who might benefit from this novel approach to helping to develop social awareness in autism, please do not hesitate to contact me for further information 
I have a 10 year old daughter who has outbursts with prolonged crying almost like tantrums that 2 year olds have when they cannot express themselves 
I had her in therapy from age 6-8 years old for the same thing but I feel that the sessions didn't really help much 
She has severe sensitivities to light, sound, vibration, frequencies which trigger irritability and crying 
We changed her diet and tried getting her involved with activities but she is anti-social and prefers reading than being social  She is terrified of change even in daily routine (even that will trigger prolonged crying) 
It frustrates me because I don't know what else to do with her behavior 
I've tried acupuncture (she refused at the first session); she refuses massage too 
She is an honor-roll student at school and has very minimal issues at school but if she has had a bad day it does result in a tantrum or crying and defiance 
How can I get her tested for Asperger's Syndrome?
Last night our 24 year old son with Aspergers told his dad and I that he is pulling out of the 4 college classes that he recetnly enrolled in because he has not been attending class or turning in his assignments  He paid $2800 (his own money) for tuition and I reminded him of this when he told us but it did not seem to bother him 
This is the 3rd time he has started college courses and has not completed them  (He also took some concurrent college classes while he was in high school that he failed)  This is a son who basically had a 4 0 grade point average through 10th grade and got a 34 on the ACT the first time he took it 
With the news that he was once again not sticking with college courses I did not sleep well  When I got up this mornning I began looking online for help in how to deal with his situation  I found your "Launching Adult Children With Aspergers" and purchased it  Most of what is included are things we have done or did with our son throughout his life  I was hoping for more help so I am emailing you now in hopes of more specific ideas 
We noticed some things with our son, Taylor, as a yound child but as we had not heard of Aspergers at that time we just did what we thought would help him  As a toddler and a child at pre-school he generally went off on his own to play  When I talked to his pre-school teacher about my concerns (that I was worried he would end up a hermit) she said she did not see him being a loner and that he seemed to interact fine with others in many situations  We worked with him on making eye contact when talking with others  We explained different emotions in people's faces and mannerisms to help him know how to interact with others  We discussed the fact that people would say things that did not mean what they souneded like - such as "I'm so hungry I could eat a horse"  As we did these things he worked hard to better understand communication with others 
During his 4th grade year I had a teacher from the gifted program ask me if I had ever heard of Aspergers  I told her that I had not heard of it  She proceeded to read me some of the charateristics and so many of them described my son  So we had him tested by the school district during the summer between 4th and 5th grade and they did find that he had Aspergers but that he was high functioning  We then set him up with and EIP which stayed with him until his sophomore year  We pulled him from it at that time because we had moved and the new district was requiring him to take one class a day that was a study class  This reduced the number of required classes he could take and he was doing fine with his studies at the time 
It was during the 2nd half of his Junior year that we noticed some of his grades going down  Then during his Senior year is when he started skipping classes and not doing assignments  We had not realized it before then but we soon became aware that he was addicted to gaming  He would go to the library or somewhere else on campus and play games on the computer rather than go to class  It was also at this time that he began lying about his actions (so as not to get in trouble) 
Based on his grades and his ACT score he received offers from colleges for full tuition scholarships  He chose the college where he had taken concurrent classes during his high school years  But he proceeded to skip class and not turn in assignments so he lost his scholarship and quit attending college  During this time he was only able to find employment through an employment agency where he was mostly sent to manuel labor type jobs (which is not something he enjoys but he did it anyway)  It was during this time that at one place had gone to on numerous occasions he was told if he came late one more time they would tell the emplyment agency they did not want him to come there anymore  (This seemed to make an impression on him because he has continued to be reliable and responsbile at his places of employment) 
At 19 1/2 he left to serve a 2 year full-time mission for our church  He completed his mission successfully  (I don't think it was without some struggle, stress and depression, but he was able to pick himself up and move on from those times) 
When he came home he started working for the employment agency again but began looking for employment elsewhere  He got a job at a local Chick Fil-A where he has worked for 3 years  He started college again shortly after he came home but as before it was short lived  He did finish out the semester but failed most of the classes due to his skipping class and not turning in assignments  When he skipped class he would usually sleep in his car 
Taylor's life consists of working (where to the best of our knowledge) he does well, he is reliable and his employer likes him  When he comes home from work he either sleeps or plays video games or other games - such as kakuro  He spendes most of his time in the basement where his bedroom is and this is where he games  Taylor owns his own car, bought his own laptop and very rarely spends money  He pays us $200 /month to still live at home, unloads the dishwasher on a regular basis and does the weekly garbage  However, his room is a mess and he only cleans his bathroom when I tell him he needs to clean it 
Taylor used to read quite a bit and loved to learn  It has just been in his adult years that he has not read as much - I think because of his gaming addiction  Taylor goes to church on a regular basis but sleeps through the main meeting  In Sunday class room settings he stays awake - I think because he is able to particpate in discussions 
Taylor has only had 2 real friends since entering Junior High school  And as of now he only keeps in contact with one of them who still lives in Georgia  We have lived in Utah since the summer of 2007 and he has never had a friend to do things with since we have lived here  He has two younger siblings, a brother 22 and a sister 20  They love Taylor and spend time with him when they are home  They are both at college and doing well 
Throughout Taylor's school years he has seen a counsleor on a fairly regular basis  One summer during junior high he attended a weekly class where he interacted with other kids with Aspergers  We did see a lot of change in him from this group  After he returned from his mission he went to see a counselor for a short period - this counselor tried to help him with some social skills  His dad and I went with him the first 3 or 4 times but we found out that after we quit going with him he only went a few more times and then scheduled appointments but did not show a couple of the times  We only found this out when a bill came for a "no show" appointment 
I don't know if this is too much information but were are in dire need of help for him  In the information that we purchased from you you mentioned that you do coaching for Aspergers adults  I don't know if you can help us but I thought I would check with you just in case 
Alas I think I have found your information too late to save my marriage but I am hoping to save myself 
I am currently going through a very very painful separation after a 27 year relationship with my husband whom I am convinced has aspergers syndrome  It is a long and painful story and I am desperately trying to process it all alongside dealing with a very conflictual separation  My partner is angry non communicative and totally dismissive of me and our long shared history 
He walked out last year after I discovered he had been visiting massage parlours and developed a relationship with an illegal Chinese escourt whom he subsequently moved in with  He had been seeing this woman behind my back for over 18 months  The pain of all this indescribable and his dismissal of my pain and very existence beyond belief 
Leading up to this I had been battling anxiety and depression which my husband found very hard to cope with 
Over the years of our relationship I knew something was off but I just could not put my finger on it  I often felt a complete lack of validation and empathy  Communication was also difficult as my husband was defensive and unwilling to look at issues in our marriage 
Please Mark could you help me validate some of this pain and try and make dense of 27 years of my life without drowning in fear guilt and despair about my future 
Thank you for listening and your site 
I have had problems with drunkenness, being late for school, not handing in school work, buying pot from a dealer etc  I chose to focus on the drinking and did the grounding then (grounding happened 3 times)  I also stopped sleep overs at friends 100%  I have stopped handing out money for no reason or even buying treats like chocolate 
I did lose it one evening (and didn't do the poker face) when I was trying to unplug the internet at midnight on a school night (she’s always late for school so I am trying to get her to sleep at a reasonable hour)  I was physically stopped and pushed around so I slapped my daughter (it was not hard)  This ended up with her saying she didn’t want to come home (the next day after school)  By this stage, I also had enough and didn’t go get her  I thought I am not begging  You will run out of money soon  It was quite a relief to have some peace  Daughter’s Dad was in town (from another country) and called a family meeting with the counsellor  To cut a long story short, daughter and her counsellor put it on the table that daughter wants to go live somewhere else (with her friends family) because of the stress at home with me (we live on our own) (i e  stricter rules and her bucking up against it) 
I didn’t really want this but made a compromise that daughter would go there Tues morning – Friday afternoon as the friend is an A student whereas my daughter is failing  They do the same subjects  I made the decision at the end of the day based on what is good for me – some time away from the daughter  I also thought of your book when the child went to live with the grandparents – daughter will dig her own hole over at the friend’s house  They have a week day no going out policy which made me think it is OK  I went and discussed with them the problems experienced (drinking, pot, late nights, not handing in work)
I am also trying to follow the let go of school thing per your book  I find it really difficult to remain calm when I can see daughter on her phone and watching series (when I have her on the weekends) when I know there are projects due  I hired her a private tutor once a week for help with a subject  The tutor has just fired my daughter for not handing in work and being not committed  It’s not the first time private tutoring has not been appreciated  The school give me a report back on a Friday as to whether everything is handed in  The deal is – if the work is not handed in – no pocket money and no Friday night out)  Her school is a "progressive" school and there are no repercussions for her being late or not handing in work  I would change schools if I could but there are only 8 months left of school (she turns 18 in August) 
We have just completed the first week and beginning week two of your material  We are agreeing with your take and see our son and ourselves in most of what you are saying  Prior to finding your material and starting your program we had been having extreme out of control behaviors and had to call the police because he was breaking things in our house and pushed my husband  This happened three weeks ago  After that incident we took away privileges ie  PS4, phone (which had already been taken for a few days), and friends  So, last week while doing your program he already didn’t have privileges and has continued with poor behavior – name calling, throwing things, slamming doors  We are not sure when to give privileges back  He has been given the privilege of playing with friends on occasion  His 13th birthday is tomorrow  This past weekend, for his birthday my husband and he went boar hunting  Of course we debated about it but decided to go ahead since it was his bday  We are cooking some of the meet on the grill tomorrow night for his bday and inviting a couple of his friends over for a cookout  No more gifts other than cards and balloons  We are wondering if we should go ahead and give him his privileges back and not sure how to do it  Last Friday morning we attempted to talk giving him a date to return privileges and that conversation ended with him getting angry but he gathered from our conversation that he is getting his stuff back on his bday  We are starting week 2 assignments today but not sure how to handle what was already in place  Of course, we aren’t seeing the respect and responsibility we are looking for but realize it has been a long time  We were wanting him to pay for his phone and thought it might be a good time to introduce that idea  Allowing him to earn his phone  We expect that he will be angry with this idea and not sure how to implement 
My son and myself are interested in a inpatient Aspergers program  We line in Calif which is preferable  My son is very high functioning and was diagnosed dry late  He was eight years old  He has never been in or attended a full day of class  Partially due to depression,anxiety, and trouble with his ADHD also his aversion and being bullied and of course his Aspergers  He will not attend his freshmen year due to surgery on both Achilles' tendons from walking on his toes  With physical therapy he should be ready by his sophomore year! We all feel he needs in patient therapy to give him the tools on how to work with his issues in a structured setting and a place that will give him tools for the rest of his life 
In my utter desperation to find a way to get some help for my daughter's increasingly challenging behaviour I trawled the internet to see if I could find some strategies that would provide specific methods on dealing with teenagers with Asperger's syndrome  When I came across your website, I couldn't believe that every statement you made was exactly what I have been going through with my daughter  She has just turned 14 last week, and was diagnosed with Asperger's/ Autism Spectrum Disorder 15 months ago  I have already been seeing a child psychologist for the past five months, however the methods she has been advising have not been very effective 
Our main difficulty with our daughter is her overwhelming obsession to use her cell phone (and to a lesser extent her laptop) constantly  Without any restriction, she will be on it every minute of the day, and will be awake until the early hours every day  We have tried to incorporate her input around rules as to when she has to give in her phone, but she is unwilling to compromise on a time that she should give it to us, believing that she should have unlimited use  I believe she is unable to do any adequate study or homework, as she is constantly having to look at the phone  We have tried to put rules in place that she has to give in her phone and laptop on school nights at 22:15  If she is able to do this then she is given rewards, and if she doesn't then she knows that there will be consequences  The consequence has been restricted use the following day  However, this is usually where we fail, because taking her phone away from her results in tantrums, screaming, and even threatening to harm herself  This behaviour is relentless to the point where the whole family becomes deeply distressed, and inevitably results in her getting the phone back 
This obsession is affecting her schoolwork, and more severely her eyesight  She has become very shortsighted, and her eyesight continues to deteriorate as a result of holding the phone or laptop very close, and mostly in the dark without any lights on  My husband and I have a constant battle on our hands daily, in all areas of discipline with our daughter, but our main concern is that we have been unable to find a way to minimise this obsessive behaviour centred around her phone and laptop  Please can you provide some strategies that can help us specifically with this problem 
First of all, I thank you for developing this program and I am only at the first stage of assignment 1  I have loads of books I have bought, attended psychiatrists for my son and myself, family therapy, occupational therapy, begged and prayed for change but have been dealing with behavioural issues for so long I am definitely exhausted and resentful 
I am a mum to a 15 yr old boy with ASD, dyslexia, OCD and ODD  Sorry to focus on the labels but just to give you an idea of what I am dealing with  I also have a 13 yr old son whom finds his brother’s behaviours difficult, embarassing and challenging  My husband whom is not in great health ( he had a cerebral aneurysm clamped two years ago and has two further aneurysms that are inoperable so endures fatigue, headaches and stress)  We have however a pet cat that is very social and a calming influence in the home! I was fortunate enough to have loving parents but I lost both my mum and dad in 2008 and 2015  My inlaws are elderly and quite directly say they are too old to help us so it feels we are alone in dealing with the issues we have 
I am desperate for change as the household is one of stress and anger and I feel all the control lies in my son Patrick’s hands  I am hopeful your programme can make life better for all of us but I wonder if it is too early to ask you two questions?
The first lies with what to do when Patrick goes into my other son Brendan’s room and will either turn on a light when he is sleeping, yell when he is on his phone or create some disturbance  He will not leave the room when asked to do so and the situation always escalates into yelling and Brendan attempting to physically remove him  This happens regularly and always ends badly with doors slamming, my husband being woken and myself in tears feeling the lack of control and also I admit I seem to think “Why me?” which rationally I know is of no help 
The second problem is leaving the house for school  Patrick refuses personal hygiene (either morning or night) and any request to even brush his teeth is fraught with swearing and abuse  If I can get him to shower, he will watch the water roll down the drain and turn up the water really high temp (mu husband has had to turn down the thermostat on the hot water service) without so much as getting wet  My husband leaves for work at 6am but I leave at 745 to work as a nurse in a busy outpatients department in the Alfred Hospital (Melbourne)  My work is my sanity as it is a paid break from home but most days I am late which is causing considerable stress and anxiety not to mention my responsibility to do my job  Patrick simply refuses to leave the house and as much as I am tempted to just walk out and leave I know the house would be left unlocked and wonder if Patrick would even attend school  The time I need to leave is not negotiable but Patrick uses this to his advantage and seems to delight in stressing me out and subsequently speeding to work in a frazzled mess 
The interesting and frustrating element in all of this is that although he is socially isolated at school (he has no friends) and academically challenged his behaviour at school is not a problem  He is quiet and his teachers report he does his best and is compliant and well mannered  It is like a Jekyll and Hyde situation where another side of him at home is so angry and abusive yet at school this behaviour does not happen 
I’m Jackie, I now work primarily as a freelance tech writer, after starting my career in software development and moving on to teach IT to young adults at a variety of colleges and schools 
My freelance work is pretty varied and looks at many aspects of the computer industry as a whole, and I’ve just recently completed a piece which gives help and advice to anyone wanting to become a game designer, which you can read here: http://www gamedesigning org/become-a-game-designer/  It highlights the hard work and effort it takes to get into such a role, and also how you can further your career and continue to learn and improve as you go  I hope you’ll agree it shows that starting work in the industry takes dedication and skill and that becoming a game designer isn’t just a fly-by-night job!
If you’d be interested in sharing a quick mention of my work on your blog that would be really wonderful and I’d appreciate the chance to get my work out there to a wider audience  Alternatively, I’d be happy to write a short blurb or paragraph or two (or a longer piece - just let me know) highlighting the key points because I think some of your readers might get a lot of value from it 
My son just turned 15 and is a freshman in high school  Although this is his first year in a general ed environment, he is struggling with behaviors in school  He has meltdowns and does not express why he would have them until much later  Once we all know what caused it, the school will accommodate him and try to "change up" things so as not to cause his meltdown  Once that is resolved, another issue comes up and causes him to melt down  He is a high functioning and academically does well, when he wants to do the work  We battle at home over homework  He does not care how it is done, as long as he hands it in  He thinks failing a test is ok, at least he took the test  Homework is never on his mind when he gets home from school  If I never prompt him, he would never open is backpack  He can be aggressive but is never intentionally trying to hurt anyone  He may push over a chair in school, but it is not directed at anyone  We know how that in itself could hurt someone who gets hit by it though  He is defiant in that he only wants to do what interests him  He does not go out by himself (still immature), or abuse alcohol or drugs and never curses  He is a very funny kid and very talented  His main problems are task avoidance and seeking attention  He can be disrespectful to adults in that he is "cheeky" with them, trying to be funny or cute  And he has no "filters" 
I’ve just finished reading your Living with an Aspergers Partner ebook  I found it so informative, thank you 
You offered some personal advise, and i wanted to run a situation past you and seek your input as to a strategy for what to do next 
I’ve been seeing a guy for about 7 months now who I believe has Aspergers  I came to this conclusion months ago and I don’t think he realizes, (or acknowledges) although he is aware he has some traits 
He’s highly intelligent and successful, a pattern seeker, has a tendency to focus on the project to hand to the total exclusion of all else for as long sit takes (work or home) socially awkward (has learned coping strategies), sensitive to loud noise, high anxiety with control strategies, black and white thinking etc  He’s currently not working and I’ve seen a slow withdrawal over the last 6 weeks, including the need to ‘escape’ and leave a situation at least once 
He also has a bipolar ex overseas who has primary custody one daughter where there has been ongoing patterns of drama which has recently increased 
Over the past couple of months (since stopping work and drama increase) I’ve gone from being ‘wonderful’ in his eyes to him now being sorry and not having the ‘urge’ to spend close/intimate time with me and offering friendship  Since he shared that with me in a message he’s stonewalled and has retreated to the safety of minimal messages and talks about not knowing what best to say and not being able to find the right words somehow 
He’s a good kind man who I feel is struggling  I’m concerned about his anxiety and possibly the risk of depression  I’m fairly resilient and whilst i’m disappointed he doesn’t want to pursue a relationship with me, i’m concerned for him and his well being  One of his very few close friends is also just leaving the country to live overseas 
The strategy I’ve used so far is simply to back off and give him space  I’ve asked to take him up on an original offer he made to talk but haven’t pushed it  I also haven’t been aggressive or accusatory in the few messages i’ve sent 
Any advise you could give would be greatly appreciated,
Carli who is 10 years old and has had behavioral issues her whole life  The other night she came home very upset after having a conflict with a friend  She was at her friend's house and her and her friend wanted to get on the computer and the older sister was using it  Carli made up a story that someone was at the door to get the older sister off the computer  Her friend didn't understand that she was making up a story to get the sister off the computer  She got excited that someone was at the door and ran downstairs to answer the door  In the process of getting the door, she fell and yelled at Carli  Carli became extremely upset  She was able to control her feelings at her friend's house, but when she came home, she proceeded to cry extremely loudly for over an hour  Her dad spent most of that time with her, talking to her and trying to calm her down  After an hour, I asked him if he could please tell her to be more quiet because the other members of the household were trying to go to sleep 
My question is    how do I as the girlfriend, handle this? He did not like that I asked her to be quiet  We have a rule that if she is having bad behavior, and can't calm down in 5 minutes, he takes her out of the house because her yelling doesn't stop for a long time and is very upsetting to everyone in the household  I would like to ask him to do this with this kind of situation as well  Is this a reasonable request? His thought was that she shouldn't be made to calm down, because everyone handles being upset in a different way  But, she was literally sobbing and wailing very loudly 
My other question is should she have been told that if she wouldn't have lied, this wouldn't have happened? She has a history of lying and of not accepting responsibility for her actions  My boyfriend became very upset with me when I brought this up  He was being very sympathetic and understanding to her  I feel like he was giving her negative attention, and being an over indulgent parent by not putting his foot gown and saying, "you can't carry on like this, even though you are upset"  Please let me know how we can handle these situations better 
I am contacting you for help with adult AS  I am taking initiative to pre screen potential therapists to help my current boyfriend get therapy and help with Adult AS 
He has seen many therapists, but it seems like they aren’t really helping him with his problems  They don’t seem to understand how his (undiagnosed) AS would affect therapy approaches  For example, he may not share enough in therapy session and I’m assuming an AS therapist would recognize that is part of the AS and employ strategies to get information from him that helps with treatment  Sometime he tunes out when he is processing something heavy or that he doesn’t want to hear necessarily, or he gets distracted and I’m hoping an As therapist would recognize that and get that he may need repeated something for example, if this is happening 
He is currently suffering from depression that appears clinical in nature as well as reoccurring negative thoughts about something specific that has been worrying him about our relationship  Today he told me these reoccurring thoughts happen during all waking hours unless he watches TV, he never gets a break from them and they make him feel like he is going crazy  As his girlfriend, I am extremely concerned that he cannot get relief from these thoughts and that the therapists he is seeing are unable to help him with his problems  Therefore, I am taking initiative to try and help him find better therapy options, because I want to see him someone who can better help him get to the bottom of things and help him with the challenges he is facing  He really needs an advocate that will help him go deep to figure things out and not just assume therapies are working well, without seeing changes or getting supporting feedback from him in that regard 
Here are some questions I am trying to ask in advance to find the right people to help us with this  As you may know, insurance for these therapies are not often available  We don’t have a lot of money to go from therapist to therapist to find the right person and are hoping prescreening will help 
I recently downloaded your e-book and listened to your talks and your information is by far the most helpful I have been able to find to date  It's very accurately describes my situation as an NT wife married to a very probable AS husband  I think you for taking the time to write this and sharing your insights as well as the experiences of many of your clients  It has really helped me understand the last 32 years of our marriage and get a grasp on how to move forward 
One area that is of primary concern to me, that I did not see addressed, is stimming  I believe that is the behavior my husband is showing through constant vocal singing, repetition of words, shouting out, as well as slapping himself in the chest and general nervous activity  It is very loud and disruptive to our household and it is often a relief when he is not at home  I think there may be a level of Tourette's syndrome as well 
I did some searches on the Internet and could not find anything that really describes his behavior  Most of what I found was flapping or children's behavior  I understand that it is a release of nervous tension but I am really trying to find some strategies to help him stop this behavior as it is extremely frustrating and builds my resentment in dealing with it daily  A lot of it is embarrassing as well and sounds childish to me 
He usually does this when close family members are around and will reign himself in if he is around other people besides us  When we are home it is constant  He also has a lot of anger, mostly at himself, and blows up at unimportant things, it is as if he has a ton of negative energy inside him that need to get out and stimming is one outlet 
I will try to build my acceptance of it, but I also would just like him to stop especially the loudest and most annoying portions  Would you have any resources you could point me to?



ground_truth: A study on the effects of Brazilian Jiu Jitsu and psychotherapy on people with autism.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: How does the performance of the PLM with decimation compare to other methods?

Read the following text and answer briefly.

Context 2: \section{Introduction}
Given a data set and a model with some unknown parameters, the inverse problem aims to find the values of the model parameters that best fit the data   
In this work, in which we focus on systems of interacting elements,
 the inverse problem concerns  the statistical inference
 of the underling interaction network and of its coupling coefficients from observed data on the dynamics  of the system  
 Versions of this problem are encountered in physics, biology (e g , \cite{Balakrishnan11,Ekeberg13,Christoph14}), social sciences and finance (e g ,\cite{Mastromatteo12,yamanaka_15}), neuroscience (e g , \cite{Schneidman06,Roudi09a,tyrcha_13}), just to cite a few, and are becoming more and more important due to the increase in the amount of data available from these fields \\
 \indent 
 A standard approach used in statistical inference is to predict the interaction couplings by maximizing the likelihood function 
 This technique, however, requires the evaluation of the  
 
   partition function that, in the most general case, concerns a number of computations scaling exponentially with the system size 
  
  
    Boltzmann machine learning uses Monte Carlo sampling to compute the gradients of the Log-likelihood looking for stationary points \cite{Murphy12} but this method is computationally manageable only for small systems  A series of faster approximations, such as naive mean-field, independent-pair approximation \cite{Roudi09a, Roudi09b}, inversion of TAP equations \cite{Kappen98,Tanaka98}, small correlations expansion \cite{Sessak09}, adaptive TAP \cite{Opper01}, adaptive  cluster expansion \cite{Cocco12} or Bethe approximations \cite{Ricci-Tersenghi12, Nguyen12}  have, then, been developed  These techniques take as input means and correlations of observed variables and most of them assume a fully connected graph as underlying connectivity network, or expand  around it by perturbative dilution   In most cases, network reconstruction turns out to  be not accurate for small data sizes and/or when couplings are  strong or, else, if the original interaction network is sparse \\
\indent
 A further method, substantially improving performances for small data, is the so-called Pseudo-Likelyhood Method (PLM) \cite{Ravikumar10}  In Ref  \cite{Aurell12} Aurell and Ekeberg performed a comparison between PLM and some of the just mentioned mean-field-based algorithms on the pairwise interacting Ising-spin  ($\sigma = \pm 1$) model, showing how PLM performs sensitively better, especially on sparse graphs and in the high-coupling limit, i e , for low temperature 
 
 In this work, we aim at performing statistical inference  on a model whose interacting variables are continuous $XY$ spins, i e , $\sigma \equiv \left(\cos \phi,\sin \phi\right)$ with $\phi \in [0, 2\pi )$  The developed tools can, actually, be also straightforward applied  to the $p$-clock model  \cite{Potts52} where the phase $\phi$ takes discretely equispaced $p$ values  in the $2 \pi$ interval, $\phi_a =  a 2 \pi/p$, with $a= 0,1,\dots,p-1$  The $p$-clock model, else called vector Potts model, gives a hierarchy of discretization of the $XY$ model as $p$ increases  For $p=2$, one recovers the Ising model, for $p=4$ the Ashkin-Teller model \cite{Ashkin43}, for $p=6$ the ice-type model \cite{Pauling35,Baxter82} and the eight-vertex model \cite{Sutherland70,Fan70,Baxter71} for $p=8$   
It turns out to be very useful also for numerical implementations of the continuous $XY$ model  
Recent analysis on the multi-body $XY$ model has shown that for a limited number of discrete phase values ($p\sim 16, 32$) the thermodynamic critical properties of the $p\to\infty$ $XY$ limit are promptly recovered \cite{Marruzzo15, Marruzzo16}   
Our main motivation to study statistical inference is that these kind of models have recently turned out to be rather useful in describing the behavior of optical systems, 
including standard mode-locking lasers \cite{Gordon02,Gat04,Angelani07,Marruzzo15} and random lasers \cite{Angelani06a,Leuzzi09a,Antenucci15a,Antenucci15b,Marruzzo16}  
In particular, the inverse problem on the pairwise XY model analyzed here might be of help in recovering images from light propagated through random media  


      This paper is organized as follows: in Sec  \ref{sec:model} we introduce the general model  and we discuss its  derivation also  as a model for light transmission through random scattering media  
    In Sec  \ref{sec:plm} we introduce the PLM with $l_2$ regularization  and with decimation, two variants of the PLM respectively introduced in Ref  \cite{Wainwright06} and \cite{Aurell12} for the inverse Ising problem  
    Here, we analyze these techniques for continuous $XY$ spins and we test them on thermalized data generated by Exchange Monte Carlo numerical simulations of the original model dynamics  In Sec  \ref{sec:res_reg} we  present the results related to the PLM-$l_2$  In Sec  \ref{sec:res_dec} the results related to the PLM with decimation are reported and its performances are compared to the PLM-$l_2$ and to a variational mean-field method analyzed in Ref  \cite{Tyagi15}  In Sec  \ref{sec:conc}, we outline conclusive remarks and perspectives 

        \section{The leading $XY$ model}
      \label{sec:model}
 The leading model we are considering is defined, for a system of $N$ angular $XY$ variables, by the Hamiltonian 
 \begin{equation}
  \mathcal{H} = - \sum_{ik}^{1,N} J_{ik} \cos{\left(\phi_i-\phi_k\right)} 
  \label{eq:HXY}
 
  \end{equation} 
  
  The $XY$ model is well known in statistical mechanics, displaying important physical
  insights, starting from the Berezinskii-Kosterlitz-Thouless
  transition in two dimensions\cite{Berezinskii70,Berezinskii71,Kosterlitz72} and moving to, e g , the
  transition of liquid helium to its superfluid state \cite{Brezin82}, the roughening transition of the interface of a crystal in equilibrium with its vapor \cite{Cardy96}  In presence of disorder and frustration \cite{Villain77,Fradkin78} the model has been adopted to describe synchronization problems as the Kuramoto model \cite{Kuramoto75} and in the theoretical modeling of Josephson junction arrays \cite{Teitel83a,Teitel83b} and arrays of coupled lasers \cite{Nixon13} 
  Besides several derivations and implementations of the model in quantum and classical physics, equilibrium or out of equilibrium, ordered or fully frustrated systems, Eq  (\ref{eq:HXY}), in its generic form,
  has found applications also in other fields  A rather fascinating example being the behavior of starlings flocks  \cite{Reynolds87,Deneubourg89,Huth90,Vicsek95, Cavagna13} 
  Our interest on the $XY$ model resides, though, in optics  Phasor and phase models with pairwise and  multi-body interaction terms can, indeed, describe the behavior of electromagnetic modes in both linear and nonlinear optical systems in the analysis of problems such as light propagation and lasing \cite{Gordon02, Antenucci15c, Antenucci15d}  As couplings are strongly frustrated, these models turn out to be especially useful to the study of optical properties in random media \cite{Antenucci15a,Antenucci15b}, as in the noticeable case of random lasers \cite{Wiersma08,Andreasen11,Antenucci15e}  and they might as well be applied to linear scattering problems, e g , propagation of waves in opaque systems or disordered fibers  
  
  
  \subsection{A propagating wave model}
  We briefly mention a derivation of the model as a proxy for the propagation of light through random linear media  
 Scattering of light is held responsible to obstruct our view and make objects opaque  Light rays, once that they enter the material, only exit  after getting scattered multiple times within the material  In such a disordered medium, both the direction and the phase of the propagating waves are random  Transmitted light 
 yields a disordered interference pattern typically  having low intensity, random phase and almost no resolution, called a speckle  Nevertheless, in recent years it has been realized that disorder is rather a blessing in disguise \cite{Vellekoop07,Vellekoop08a,Vellekoop08b}  Several experiments have made it possible to control the behavior of light and other optical processes in a given random disordered medium,  
 by exploiting, e g ,  the tools developed for wavefront shaping to control the propagation of light and to engineer the confinement of light \cite{Yilmaz13,Riboli14} 
 \\
 \indent
 In a linear dielectric medium, light propagation can be described through a part of the scattering matrix, the transmission matrix $\mathbb{T}$, linking the outgoing to the incoming fields  
 Consider the case in which there are $N_I$ incoming channels and $N_O$ outgoing ones; we can indicate with $E^{\rm in,out}_k$ the input/output electromagnetic field phasors of channel $k$  In the most general case, i e , without making any particular assumptions on the field polarizations, each light mode and its polarization polarization state can be represented by means of the $4$-dimensional Stokes vector  Each $ t_{ki}$ element of $\mathbb{T}$, thus, is a $4 \times 4$ M{\"u}ller matrix  If, on the other hand, we know that the source is polarized and the observation is made on the same polarization, one can use a scalar model and adopt Jones calculus \cite{Goodman85,Popoff10a,Akbulut11}:
   \begin{eqnarray}
 E^{\rm out}_k = \sum_{i=1}^{N_I}  t_{ki} E^{\rm in}_i \qquad \forall~ k=1,\ldots,N_O
 \label{eq:transm}
 \end{eqnarray}
  We recall that the elements of the transmission matrix are random complex coefficients\cite{Popoff10a}  For the case of completely unpolarized modes, we can also use a scalar model similar to Eq  \eqref{eq:transm}, but whose variables are  the intensities of the outgoing/incoming fields, rather than the fields themselves \\ 
In the following, for simplicity, we will consider Eq  (\ref{eq:transm}) as our starting point,
where $E^{\rm out}_k$, $E^{\rm in}_i$ and $t_{ki}$ are all complex scalars  
If Eq  \eqref{eq:transm} holds for any $k$, we can write:
  \begin{eqnarray}
  \int \prod_{k=1}^{N_O} dE^{\rm out}_k \prod_{k=1}^{N_O}\delta\left(E^{\rm out}_k - \sum_{j=1}^{N_I}  t_{kj} E^{\rm in}_j \right) = 1
  \nonumber
  \\
  \label{eq:deltas}
  \end{eqnarray}

 Observed data are a noisy representation of the true values of the fields  Therefore, in inference problems it is statistically more meaningful to take that noise into account in a probabilistic way, 
 rather than looking  at the precise solutions of the exact equations (whose parameters are unknown)  
 To this aim we can introduce Gaussian distributions whose limit for zero variance are the Dirac deltas in Eq  (\ref{eq:deltas}) 
 Moreover, we move to consider the ensemble of all possible solutions of Eq  (\ref{eq:transm}) at given $\mathbb{T}$, looking at  all configurations of input fields  We, thus, define the function:
 
   \begin{eqnarray}
  Z &\equiv &\int_{{\cal S}_{\rm in}} \prod_{j=1}^{N_I}  dE^{\rm in}_j \int_{{\cal S}_{\rm out}}\prod_{k=1}^{N_O} dE^{\rm out}_k 
  \label{def:Z}
\\
    \times
  &&\prod_{k=1}^{N_O}
   \frac{1}{\sqrt{2\pi \Delta^2}}  \exp\left\{-\frac{1}{2 \Delta^2}\left|
  E^{\rm out}_k -\sum_{j=1}^{N_I}  t_{kj} E^{\rm in}_j\right|^2
\right\} 
\nonumber
 \end{eqnarray}
   We stress that the integral of Eq  \eqref{def:Z} is not exactly a Gaussian integral  Indeed, starting from Eq  \eqref{eq:deltas}, two constraints on the electromagnetic field intensities must be taken into account  

  The space of solutions is  delimited by the total power ${\cal P}$ received by system, i e , 
  ${\cal S}_{\rm in}: \{E^{\rm in} |\sum_k I^{\rm in}_k = \mathcal{P}\}$, also implying  a constraint on the total amount of energy that is transmitted through the medium, i  e , 
  ${\cal S}_{\rm out}:\{E^{\rm out} |\sum_k I^{\rm out}_k=c\mathcal{P}\}$, where the attenuation factor  $c<1$ accounts for total losses 
  As we will see more in details in the following, being interested in inferring the transmission matrix through the PLM, we can omit to explicitly include these terms in Eq  \eqref{eq:H_J} since they do not depend on $\mathbb{T}$ not adding any information on the gradients with respect to the elements of $\mathbb{T}$ 
  
 Taking the same number of incoming and outcoming channels, $N_I=N_O=N/2$, and  ordering the input fields in the first $N/2$ mode indices and the output fields in the last $N/2$ indices, we can drop the ``in'' and ``out'' superscripts and formally write $Z$  as a partition function
    \begin{eqnarray}
        \label{eq:z}
 && Z =\int_{\mathcal S} \prod_{j=1}^{N} dE_j \left(   \frac{1}{\sqrt{2\pi \Delta^2}} \right)^{N/2} 
 \hspace*{- 4cm} \exp\left\{
  -\frac{ {\cal H} [\{E\};\mathbb{T}] }{2\Delta^2}
  \right\}
  \\
&&{\cal H} [\{E\};\mathbb{T}] =
-  \sum_{k=1}^{N/2}\sum_{j=N/2+1}^{N} \left[E^*_j t_{jk} E_k + E_j t^*_{kj} E_k^* 
\right]
 \nonumber
\\
&&\qquad\qquad \qquad + \sum_{j=N/2+1}^{N} |E_j|^2+ \sum_{k,l}^{1,N/2}E_k
U_{kl} E_l^*
 \nonumber
 \\
 \label{eq:H_J}
 &&\hspace*{1 88cm } = - \sum_{nm}^{1,N} E_n J_{nm} E_m^*
 \end{eqnarray}
 where ${\cal H}$ is a real-valued function by construction, we have introduced the effective input-input coupling matrix
\begin{equation}
U_{kl} \equiv \sum_{j=N/2+1}^{N}t^*_{lj} t_{jk} 
 \label{def:U}
 \end{equation}
 and the whole interaction matrix reads (here $\mathbb{T} \equiv \{ t_{jk} \}$)
 \begin{equation}
 \label{def:J}
 \mathbb J\equiv \left(\begin{array}{ccc|ccc}
 \phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}\\
 \phantom{()}&-\mathbb{U} \phantom{()}&\phantom{()}&\phantom{()}&{\mathbb{T}}&\phantom{()}\\
\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}\\
 \hline
\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}&\phantom{()}\\
 \phantom{()}& \mathbb   T^\dagger&\phantom{()}&\phantom{()}& - \mathbb{I} &\phantom{()}\\
\phantom{a}&\phantom{a}&\phantom{a}&\phantom{a}&\phantom{a}&\phantom{a}\\
 \end{array}\right)
 \end{equation}
 
 Determining the electromagnetic complex amplitude configurations that minimize the {\em cost function} ${\cal H}$, Eq   (\ref{eq:H_J}),  means to maximize the overall distribution peaked around the solutions of the transmission Eqs  (\ref{eq:transm})  As the variance $\Delta^2\to 0$, eventually, the initial set of Eqs  (\ref{eq:transm}) are recovered  The ${\cal H}$ function, thus, plays the role of an Hamiltonian and  $\Delta^2$ the role of a noise-inducing temperature  The exact numerical problem corresponds to the zero temperature limit of the statistical mechanical problem  Working with real data, though, which are noisy, a finite ``temperature''
  allows for a better representation of the ensemble of solutions to the sets of equations of continuous variables  
  

  
  
  Now, we can express every phasor in Eq  \eqref{eq:z}  as $E_k = A_k e^{\imath \phi_k}$  As a working hypothesis we will consider the intensities $A_k^2$ as either homogeneous or as \textit{quenched} with respect to phases 
The first condition occurs, for instance, to the input intensities $|E^{\rm in}_k|$ produced by a phase-only spatial light modulator (SLM) with homogeneous illumination \cite{Popoff11} 
With \textit{quenched} here we mean, instead, that the intensity of each mode is the same for every solution of Eq  \eqref{eq:transm} at fixed $\mathbb T$ 
We stress that, including intensities in the model does not preclude the inference analysis but it is out of the focus of the present work and will be considered elsewhere  

If all intensities are uniform in input and in output, this amount to a constant rescaling for each one of the four sectors of matrix $\mathbb J$ in Eq  (\ref{def:J}) that will not change the properties of the matrices 
For instance, if the original transmission matrix is unitary, so it will be the rescaled one and the matrix $\mathbb U$ will be  diagonal 
Otherwise, if intensities are \textit{quenched}, i e , they can be considered as constants in Eq  (\ref{eq:transm}),
they are inhomogeneous with respect to phases  The generic Hamiltonian element will, therefore, rescale as 
  \begin{eqnarray}
  E^*_n J_{nm} E_m = J_{nm} A_n A_m e^{\imath (\phi_n-\phi_m)} \to J_{nm} e^{\imath (\phi_n-\phi_m)}
  \nonumber
  \end{eqnarray}
  and the properties of the original  $J_{nm}$ components are not conserved  in the rescaled one  In particular, we have no argument, anymore, to possibly set the rescaled $U_{nm}\propto \delta_{nm}$ 
  Eventually, we end up with the complex couplings $XY$ model, whose real-valued Hamiltonian is written as
 \begin{eqnarray}
  \mathcal{H}& = &  - \frac{1}{2} \sum_{nm} J_{nm} e^{-\imath (\phi_n - \phi_m)}  + \mbox{c c } 
    \label{eq:h_im}
\\    &=&  - \frac{1}{2} \sum_{nm} \left[J^R_{nm} \cos(\phi_n - \phi_m)+
  J^I_{nm}\sin (\phi_n - \phi_m)\right] 
  \nonumber
 \end{eqnarray}
where $J_{nm}^R$ and $J_{nm}^I$ are the real and imaginary parts of $J_{nm}$  Being $\mathbb J$  Hermitian, $J^R_{nm}=J^R_{mn}$ is symmetric and $J_{nm}^I=-J_{mn}^I$ is skew-symmetric 

\begin{comment}
\textcolor{red}{
F: comment about quenched:
I think that to obtain the XY model, it is not necessary that the intensities are strictly quenched (that is also a quite unfeasible situation, I guess) 
Indeed eq (2) does not deal with the dynamics of the modes, but just connect the in and out ones 
For this, what it is necessary to have the XY model, it is that the intensities are always the same on the different samples
(so that the matrix $t_{ij}$ is the same for different phase data)  If the intensities are fixed, then they can be incorporated in $t_{ij}$ and eq (2) can be written just for phases as described  \\
}
\end{comment}


  \section{Pseudolikelihood Maximization}
  \label{sec:plm}
The inverse problem consists in the reconstruction of the parameters $J_{nm}$ of the Hamiltonian, Eq  (\ref{eq:h_im})   
Given a set of $M$ data configurations of $N$ spins
 $\bm\sigma = \{ \cos \phi_i^{(\mu)},\sin \phi_i^{(\mu)} \}$, $i = 1,\dots,N$ and $\mu=1,\dots,M$, we want to \emph{infer} the couplings:
 \begin{eqnarray}
\bm \sigma  \rightarrow  \mathbb{J} 
\nonumber
 \end{eqnarray}
 With this purpose in mind,
 in the rest of this section we implement the working equations for the techniques used  
 In order to test our methods, we generate the input data, i e , the configurations, by Monte-Carlo simulations of the model 
 The joint probability distribution of the $N$ variables $\bm{\phi}\equiv\{\phi_1,\dots,\phi_N\}$, follows the Gibbs-Boltzmann distribution:
 \begin{equation}\label{eq:p_xy}
 P(\bm{\phi}) = \frac{1}{Z} e^{-\beta \mathcal{H\left(\bm{\phi}\right)}} \quad \mbox{ where } \quad Z = \int \prod_{k=1}^N d\phi_k  e^{-\beta \mathcal{H\left(\bm{\phi}\right)}}  
 \end{equation}
 and where we denote $\beta=\left( 2\Delta^2 \right)^{-1}$ with respect to Eq  (\ref{def:Z}) formalism 
 In order to stick to usual statistical inference notation, in the following we will rescale the couplings by a factor $\beta / 2$: $\beta J_{ij}/2 \rightarrow J_{ij}$  
 The main idea of the PLM is to work with the conditional probability distribution of one variable $\phi_i$ given all other variables, 
 $\bm{\phi}_{\backslash i}$:
 
  \begin{eqnarray}
	\nonumber
   P(\phi_i | \bm{\phi}_{\backslash i}) &=& \frac{1}{Z_i} \exp \left \{ {H_i^x (\bm{\phi}_{\backslash i})
  	\cos \phi_i + H_i^y (\bm{\phi}_{\backslash i}) \sin \phi_i } \right \}
	\\
 \label{eq:marginal_xy}
	&=&\frac{e^{H_i(\bm{\phi}_{\backslash i}) \cos{\left(\phi_i-\alpha_i(\bm{\phi}_{\backslash i})\right)}}}{2 \pi I_0(H_i)}
  \end{eqnarray}
  where $H_i^x$ and $H_i^y$ are defined as
   \begin{eqnarray}
   H_i^x (\bm{\phi}_{\backslash i})  &=& \sum_{j (\neq i)} J^R_{ij} \cos \phi_j  - \sum_{j  (\neq i) } J_{ij}^{I} \sin \phi_j \phantom{+  h^R_i} \label{eq:26} \\
   H_i^y  (\bm{\phi}_{\backslash i})  &=&  \sum_{j  (\neq i)} J^R_{ij}  \sin \phi_j  + \sum_{j  (\neq i) } J_{ij}^{I}   \cos \phi_j \phantom{ + h_i^{I} }\label{eq:27}
   \end{eqnarray}
and $H_i= \sqrt{(H_i^x)^2 + (H_i^y)^2}$, $\alpha_i = \arctan H_i^y/H_i^x$   and we introduced the modified Bessel function of the first kind:
  \begin{equation}
  \nonumber
   I_k(x) = \frac{1}{2 \pi}\int_{0}^{2 \pi} d \phi e^{x \cos{ \phi}}\cos{k \phi}
  \end{equation}
  
   Given $M$ observation samples $\bm{\phi}^{(\mu)}=\{\phi^\mu_1,\ldots,\phi^\mu_N\}$, $\mu = 1,\dots, M$, the
   pseudo-loglikelihood for the variable $i$ is given by the logarithm of Eq  (\ref{eq:marginal_xy}),
   \begin{eqnarray}
   \label{eq:L_i}
   L_i &=& \frac{1}{M}  \sum_{\mu = 1}^M  \ln P(\phi_i^{(\mu)}|\bm{\phi}^{(\mu)}_{\backslash i})
   \\
   \nonumber
   & =&  \frac{1}{M}  \sum_{\mu = 1}^M  \left[ H_i^{(\mu)} \cos( \phi_i^{(\mu)} - \alpha_i^{(\mu)}) - \ln  2 \pi I_0\left(H_i^{(\mu)}\right)\right] \,  
    \end{eqnarray}
The underlying idea of PLM is that an approximation of the true parameters of the model is obtained for values that maximize the functions $L_i$ 
The specific maximization scheme differentiates the different techniques 


   
   
   \subsection{PLM with $l_2$ regularization}
   Especially for the case of sparse graphs, it is useful to add a regularizer, which prevents the maximization routine to move towards high values of 
   $J_{ij}$ and $h_i$ without converging  We will adopt an $l_2$ regularization so that the Pseudolikelihood function (PLF) at site $i$  reads:
   \begin{equation}\label{eq:plf_i}
  {\cal L}_i = L_i
  - \lambda \sum_{i \neq j} \left(J_{ij}^R\right)^2 - \lambda \sum_{i \neq j} \left(J_{ij}^I\right)^2  
   \end{equation}
   with $\lambda>0$ 
   Note that the values of $\lambda$ have to be chosen arbitrarily, but not too large, in order not to overcome $L_i$ 
   The standard implementation of the PLM consists in maximizing each ${\cal L}_i$, for $i=1\dots N$, separately  The expected values of the couplings are then:
   \begin{equation}
   \{ J_{i j}^*\}_{j\in \partial i} :=  \mbox{arg max}_{ \{ J_{ij} \}}
    \left[{\cal L}_i\right]
   \end{equation}
   In this way, we obtain two estimates for the coupling $J_{ij}$, one from maximization of ${\cal L}_i$, $J_{ij}^{(i)}$, and another one from ${\cal L}_j$, say $J_{ij}^{(j)}$ 
    Since the original Hamiltonian of the $XY$ model is Hermitian, we know that the real part of the couplings is symmetric while the imaginary part is skew-symmetric  
   
     The final estimate for $J_{ij}$ can then be obtained  averaging the two results:
  
  
  
   \begin{equation}\label{eq:symm}
   J_{ij}^{\rm inferred} = \frac{J_{ij}^{(i)} + \bar{J}_{ij}^{(j)}}{2} 
   \end{equation}
   where with $\bar{J}$ we indicate the complex conjugate 
   It is worth noting that the pseudolikelihood $L_i$, Eq  \eqref{eq:L_i}, is characterized by the
   following properties: (i) the normalization term of Eq \eqref{eq:marginal_xy} can be
   computed analytically at odd with the {\em full} likelihood case that
   in general require a computational time which scales exponentially
   with the size of the systems; (ii) the $\ell_2$-regularized pseudolikelihood
   defined in Eq \eqref{eq:plf_i} is strictly concave (i e  it has a single
   maximizer)\cite{Ravikumar10}; (iii) it is consistent, i e  if $M$ samples are
   generated by a model $P(\phi | J*)$ the maximizer tends to $J*$
   for $M\rightarrow\infty$\cite{besag1975}  Note also that (iii) guarantees that  
   $|J^{(i)}_{ij}-J^{(j)}_{ij}| \rightarrow 0$ for $M\rightarrow \infty$ 
   In Secs  \ref{sec:res_reg}, \ref{sec:res_dec} 
   we report the results obtained and we analyze the performances of the PLM having taken the configurations from Monte-Carlo simulations of models whose details are known 
   

   
   \subsection{PLM with decimation}
   Even though the PLM with $l_2$-regularization allows to dwell the inference towards the low temperature region and in the low sampling case with better performances that mean-field methods, in some situations some couplings are overestimated and not at all symmetric  Moreover, in the technique there is the bias of the $l_2$ regularizer 
   Trying to overcome these problems, Decelle and Ricci-Tersenghi introduced a new method \cite{Decelle14}, known as PLM + decimation: the algorithm maximizes the sum of the $L_i$,
   \begin{eqnarray}
    {\cal L}\equiv \frac{1}{N}\sum_{i=1}^N \mbox{L}_i
    \end{eqnarray}  
    and, then, it recursively set to zero couplings which are estimated very small  We expect that as long as we are setting to zero couplings that are unnecessary to fit the data, there should be not much changing on ${\cal L}$  Keeping on with decimation, a point is reached where ${\cal L}$ decreases abruptly indicating  that relevant couplings are being decimated and under-fitting is taking place 
   Let us define  by $x$  the fraction of non-decimated couplings  To have a quantitative measure for the halt criterion of the decimation process, a tilted ${\cal L}$ is defined as,
   \begin{eqnarray}
  \mathcal{L}_t &\equiv& \mathcal{L}  - x \mathcal{L}_{\textup{max}} - (1-x) \mathcal{L}_{\textup{min}} \label{$t$PLF} 
   \end{eqnarray}
   where 
   \begin{itemize}
   \item $\mathcal{L}_{\textup{min}}$ is the pseudolikelyhood of a model with independent variables  In the XY case: $\mathcal{L}_{\textup{min}}=-\ln{2 \pi}$ 
   \item
   $\mathcal{L}_{\textup{max}}$ is the pseudolikelyhood in the fully-connected model and it is maximized over all the $N(N-1)/2$ possible couplings  
   \end{itemize}
   At the first step, when $x=1$, $\mathcal{L}$ takes value $\mathcal{L}_{\rm max}$ and  $\mathcal{L}_t=0$  On the last step, for an empty graph, i e , $x=0$, $\mathcal{L}$ takes the value $\mathcal{L}_{\rm min}$ and, hence, again $\mathcal{L}_t =0$  
   In the intermediate steps, during the decimation procedure, as $x$ is decreasing from $1$ to $0$, one observes firstly that $\mathcal{L}_t$ increases linearly and, then, it displays an abrupt decrease indicating that from this point on relevant couplings are being decimated\cite{Decelle14}  In Fig  \ref{Jor1-$t$PLF} we give an instance of this behavior for the 2D short-range XY model with ordered couplings  We notice that the maximum point of $\mathcal{L}_t$ coincides with the minimum point of the reconstruction error, the latter defined as 
   \begin{eqnarray}\label{eq:errj}
   \mbox{err}_J \equiv \sqrt{\frac{\sum_{i<j} (J^{\rm inferred}_{ij} -J^{\rm true}_{ij})^2}{N(N-1)/2}} \label{err}
   \end{eqnarray}
  We stress that the ${\cal L}_t$ maximum is obtained ignoring the underlying graph, while the err$_J$ minimum can be evaluated once the true graph has been reconstructed  
   
     \begin{figure}[t!]
   	\centering
   	\includegraphics[width=1\linewidth]{Jor1_dec_tPLF_new eps}
   	\caption{The tilted likelyhood ${\cal L}_t$ curve and the reconstruction error vs the number of decimated couplings  for an ordered, real-valued J on 2D XY model with $N=64$ spins  The peak of ${\cal L}_t$ coincides with the dip of the error }  
   	\label{Jor1-$t$PLF}
   \end{figure} 
       
   
   In the next sections we will show the results obtained on the  $XY$ model analyzing the performances of the two methods and comparing them also with a mean-field method \cite{Tyagi15} 
   
  
    
   \section{Inferred couplings with PLM-$l_2$}
    \label{sec:res_reg}
    \subsection{$XY$ model with real-valued couplings}
    
    In order to obtain the vector of couplings, $J_{ij}^{\rm inferred}$ the function $-\mathcal{L}_i$ is minimized through the vector of derivatives ${\partial \mathcal{L}_i}/\partial J_{ij}$  The process is repeated for all the couplings obtaining then a fully connected adjacency matrix  The results here presented are obtained with $\lambda = 0 01$ 
   For the minimization we have used the MATLAB routine \emph{minFunc\_2012}\cite{min_func}  
      
      \begin{figure}[t!]
    	\centering
    	\includegraphics[width=1\linewidth]{Jor11_2D_l2_JR_soJR_TPJR}
    	\caption{Top panels: instances of single site coupling reconstruction for the case of $N=64$ XY spins on a 2D lattice with ordered $J$ (left column) and bimodal distributed $J$ (right column)  
    	
    	Bottom panels: sorted couplings }
    	\label{PL-Jor1}
    \end{figure}

   
To produce the data by means of numerical Monte Carlo simulations a system with $N=64$  spin variables  is considered on a deterministic 2D lattice with periodic boundary conditions  
Each spin has then connectivity $4$, i e , we expect to infer an adjacency matrix with $N c = 256$ couplings different from zero  
The dynamics of the simulated model is based on the Metropolis algorithm and parallel tempering\cite{earl05} is used to speed up the thermalization of the system 
The thermalization is tested looking at the average energy over logarithmic time windows and
the acquisition of independent configurations
starts only after the system is well thermalized 

   For the values of the couplings we considered two cases: an ordered case, indicated in the figure as  $J$ ordered (e g , left column of Fig  \ref{PL-Jor1}) where the couplings can take values $J_{ij}=0,J$, with $J=1$, 
   and a quenched disordered case, indicated in the figures as  $J$ disordered (e g , right column of Fig  \ref{PL-Jor1})
   where the couplings can take also  negative values, i e , 
    $J_{ij}=0,J,-J$, with a certain probability   The results here presented were obtained with bimodal distributed $J$s: 
   
    $P(J_{ij}=J)=P(J_{ij}=-J)=1/2$   The performances of the PLM have shown not to depend on $P(J)$  
   
    We recall that in Sec  \ref{sec:plm} we used the temperature-rescaled notation, i e , $J_{ij}$ stands for $J_{ij}/T$  
   
    To analyze the performances of the PLM, in Fig  \ref{PL-Jor1} the inferred couplings, $\mathbb{J}^R_{\rm inf}$, are shown on top of the original couplings,  $\mathbb{J}^R_{\rm true}$ 
     The first figure (from top) in the left column shows  the $\mathbb{J}^R_{\rm inf}$ (black) and the $\mathbb{J}^R_{\rm tru}$ (green) for a given spin
     at temperature $T/J=0 7$ and number of samples  $M=1024$  PLM appears to reconstruct the correct couplings, though zero couplings are always given a small inferred non-zero value  
     In the left column of Fig   \ref{PL-Jor1},  both the $\mathbb{J}^R_{\rm{inf}}$ and the $\mathbb{J}^R_{\rm{tru}}$ are sorted in decreasing order and plotted on top of each other  
     We can clearly see that $\mathbb{J}^R_{\rm inf}$ reproduces the expected step function  Even though the jump is smeared, the difference between inferred couplings corresponding to the set of non-zero couplings 
     and to the set of zero couplings can be clearly appreciated 
     Similarly, the plots in the right column of Fig  \ref{PL-Jor1} show the results obtained for the case with  bimodal disordered couplings, for the same working temperature and number of samples  
     In particular, note that the algorithm infers half positive and half negative couplings, as expected 
     
     
\begin{figure}
\centering
\includegraphics[width=1\linewidth]{Jor11_2D_l2_errJ_varT_varM}
\caption{Reconstruction error $\mbox{err}_J$, cf  Eq  (\ref{eq:errj}), plotted as a function of temperature (left) for three values of the number of samples $M$ and  as a function $M$ (right) for three values of temperature in the ordered system, i e , $J_{ij}=0,1$  
The system size is $N=64$ }
\label{PL-err-Jor1}
\end{figure}

In order to analyze the effects of the number of samples and of the temperature regimes, we plot in Fig  \ref{PL-err-Jor1} the reconstruction error, Eq  (\ref{err}), as a function of temperature for three different sample sizes $M=64,128$ and $512$  
The error is seen to sharply rise al low temperature, incidentally, in the ordered case, for  $T<T_c \sim 0 893$, which is the Kosterlitz-Thouless transition temperature of the 2XY model\cite{Olsson92}  
 However, we can see that if only $M=64$ samples are considered, $\mbox{err}_J$ remains high independently on the working temperature  
 In the right plot of Fig  \ref{PL-err-Jor1},  $\mbox{err}_J$ is plotted as a function of $M$ for three different working temperatures $T/J=0 4,0 7$ and $1 3$  As we expect, 
 $\mbox{err}_J$  decreases as $M$ increases  This effect was observed also with mean-field inference techniques on the same model\cite{Tyagi15} 

To better understand the performances of the algorithms, in Fig  \ref{PL-varTP-Jor1} we show several True Positive (TP) curves obtained for various values of $M$ at three different temperatures $T$  As $M$ is large and/or temperature is not too small,  we are able to reconstruct correctly all the couplings present in the system (see bottom plots) 
The True Positive curve displays how many times the inference method finds a true link of the original network  as a function of the index of the vector of sorted absolute value of reconstructed couplings $J_{ij}^{\rm inf}$  
The index $n_{(ij)}$ represents the related spin couples $(ij)$  The TP curve is obtained as follows: 
first  the values $|J^{\rm inf}_{ij}|$ are sorted in descending order and  the spin pairs $(ij)$ are ordered according to the sorting position of $|J^{\rm inf}_{ij}|$  Then,
     	a cycle over the ordered set of pairs $(ij)$, indexed by $n_{(ij)}$, is performed, comparing with the original network coupling $J^{\rm true}_{ij}$ and verifying whether it is zero or not  The true positive curve is computed as
\begin{equation}
\mbox{TP}[n_{(ij)}]= \frac{\mbox{TP}\left[n_{(ij)}-1\right] (n_{ij}-1)+ 1 -\delta_{J^{\rm true}_{ij},0}}{n_{(ij)}}
\end{equation}
As far as $J^{\rm true}_{ij} \neq 0$, TP$=1$  As soon as the true coupling of a given $(ij)$ couple in the sorted list is zero, the TP curve departs from one  
In our case, where the connectivity per spin of the original system is  $c=4$ and there are $N=64$ spins, we know that we will have  $256$ non-zero couplings   
     	If the inverse problem is successful, hence, we expect a steep decrease of the TP curve when  $n_{ij}=256$ is overcome 

In Fig  \ref{PL-varTP-Jor1}
it is  shown that,  almost independently of $T/J$, the TP score improves as $M$ increases  Results are plotted for three different temperatures, $T=0 4,1$ and $2 2$, with increasing number of samples $M = 64, 128,512$ and $1024$ (clockwise)  
We can clearly appreciate the improvement in temperature if the size of the data-set is not very large: for small $M$, $T=0 4$ performs better  
When $M$ is high enough (e g , $M=1024$), instead, the TP curves do not appear to be strongly influenced by the temperature 

\begin{figure}[t!]
	\centering
	\includegraphics[width=1\linewidth]{Jor11_2D_l2_TPJR_varT_varM}
	\caption{TP  curves  for 2D short-range ordered $XY$ model with $N=64$ spins at three different values of $T/J$ with increasing - clockwise from top - $M$ }
	\label{PL-varTP-Jor1} 
\end{figure} 

\subsection{$XY$ model with complex-valued couplings}
For the complex $XY$ we have to contemporary  infer $2$ apart coupling matrices,  $J^R_{i j}$ and $J^I_{i j}$   As before, a system of $N=64$ spins is considered on a 2D lattice 
For the couplings we have considered both ordered and bimodal disordered cases 
In Fig  \ref{PL-Jor3}, a single row of the matrix $J$ (top) and the whole sorted couplings (bottom) are displayed for the ordered model (same legend as in Fig  \ref{PL-Jor1}) for the real, $J^R$ (left column), and the imaginary part, $J^I$   

\begin{figure}[t!]
	\centering
\includegraphics[width=1\linewidth]{Jor3_l2_JRJI_soJRJI_TPJRJI}
	\caption{Results related to the ordered complex XY model with $N=64$ spins on a  2D lattice  Top: instances of  single site reconstruction for the real, JR (left column), and
		the imaginary, JI (right column), part of $J_{ij}$  Bottom: sorted values of JR (left) and JI (right) }
		
	\label{PL-Jor3}
\end{figure}
 
 
  \section{PLM with Decimation}
 \label{sec:res_dec}
 

\begin{figure}[t!]
   	\centering
   	\includegraphics[width=1\linewidth]{Jor1_dec_tPLF_varT_varM}
    	\caption{Tilted Pseudolikelyhood, ${\cal L}_t$, plotted as a function of decimated couplings  Top: Different ${\cal L}_t$ curves obtained for different values of $M$ plotted on top of each other  Here $T=1 3$  The black line indicates the expected number of decimated couplings, $x^*=(N (N-1) - N c)/2=1888$  As we can see, as $M$ increases, the maximum point of ${\cal L}_t$ approaches $x^*$  Bottom: Different ${\cal L}_t$ curves obtained for different values of T with $M=2048$  We can see that, with this value of $M$, no differences can be appreciated on the maximum points of the different  ${\cal L}_t$ curves }
   	\label{var-$t$PLF}
   \end{figure}

\begin{figure}[t!]
    \centering
    \includegraphics[width=1\linewidth]{Jor1_dec_tPLF_peak_statistics_varM_prob eps}
    	\caption{Number of most likely decimated couplings, estimated by the maximum point of $\mathcal{L}_t$, as a function of the number of samples $M$  We can clearly see that the maximum point of $\mathcal{L}_t$ tends toward $x^*$, which is the right expected number of zero couplings in the system }  
    	\label{PLF_peak_statistics}
    \end{figure}
      
      For the ordered real-valued XY model we show in Fig  \ref{var-$t$PLF}, top panel, the outcome on the tilted pseudolikelyhood, $\mathcal{L}_t$ Eq  \eqref{$t$PLF}, of the progressive decimation: from a fully connected lattice  down to an empty lattice  The figure shows the behaviour of $\mathcal{L}_t$ for three different data sizes $M$  A clear data size dependence of the maximum point of  $\mathcal{L}_t$, signalling the most likely value for decimation, is shown  For small $M$ the most likely number of  couplings is overestimated and for increasing $M$ it tends to the true value, as displayed in Fig  \ref{PLF_peak_statistics}   In the bottom panel of Fig  \ref{var-$t$PLF} we display instead different 
 $\mathcal{L}_t$ curves obtained for three different values of $T$ 
  Even though the values of $\mathcal{L}_t$ decrease with increasing temperature, the value of the most likely number of decimated couplings appears to be quite independent on $T$ with $M=2048$ number of samples 
In Fig  \ref{fig:Lt_complex} we eventually display the tilted pseudolikelyhood for a 2D network with complex valued ordered couplings, where the decimation of the real and imaginary coupling matrices proceeds in parallel, that is, 
when a real coupling is small enough to be decimated its imaginary part is also decimated, and vice versa 
One can see that though the apart errors for the real and imaginary parts are different in absolute values, they display the same dip, to be compared with the maximum point of $\mathcal{L}_t$ 
     
       \begin{figure}[t!]
    	\centering
      	\includegraphics[width=1\linewidth]{Jor3_dec_tPLF_new}
      	\caption{Tilted Pseudolikelyhood, ${\cal L}_t$, plotted with the reconstruction errors for the XY model with $N=64$ spins on a 2D lattice  These results refer to the case of  ordered and complex valued couplings  The full (red) line indicates ${\cal L}_t$  The dashed (green) 
      		and the dotted (blue) lines show the reconstruction errors (Eq  \eqref{eq:errj}) obtained for the real and the imaginary couplings respectively  We can see that both ${\rm err_{JR}}$ and ${\rm err_{JI}}$ have a minimum at $x^*$ }
          	\label{fig:Lt_complex}
    \end{figure}

\begin{figure}[t!]
   	\centering
   	\includegraphics[width=1\linewidth]{Jor1_dec_JR_soJR_TPJR}
   	\caption{XY model on a 2D lattice with $N=64$ sites and real valued couplings  The graphs show the inferred (dashed black lines) and true couplings (full green lines) plotted on top of each other  The left and right columns refer to the
   		 cases of ordered and bimodal disordered couplings, respectively  Top figures: single site reconstruction, i e , one row of the matrix $J$  Bottom figures: couplings are plotted sorted in descending order }  
   	\label{Jor1_dec}
   \end{figure}
   
\begin{figure}[t!]
    	\centering
    	\includegraphics[width=1\linewidth]{Jor3_dec_JRJI_soJRJI_TPJRJI}
    	\caption{XY model on a 2D lattice with $N=64$ sites and ordered complex-valued couplings 
    		The inferred and true couplings are plotted on top of each other  The left and right columns show the real and imaginary parts, respectively, of the couplings  Top figures refer to a single site reconstruction, i e , one row of the matrix $J$  Bottom figures report the couplings sorted in descending order }
    	\label{Jor3_dec}
    \end{figure}
    
       







       \begin{figure}[t!]
     	\centering
     	\includegraphics[width=1\linewidth]{MF_PL_Jor1_2D_TPJR_varT}
     	\caption{True Positive curves obtained with the three techniques: PLM with decimation, (blue) dotted line,  PLM with $l_2$ regularization, (greed) dashed line, and mean-field, (red) full line   These results refer to real valued ordered couplings with $N=64$ spins on a 2D lattice  The temperature is here $T=0 7$ while the four graphs refer to different sample sizes: $M$ increases clockwise }
     	\label{MF_PL_TP}
     \end{figure}
    
    \begin{figure}[t!]
    	\centering
    	\includegraphics[width=1\linewidth]{MF_PL_Jor1_2D_errJ_varT_varM}
    	\caption{Variation of reconstruction error, ${\rm err_J}$, with respect to temperature as obtained with the three different techniques, see Fig  \ref{MF_PL_TP}, for four different sample size:  clockwise from top   $M=512,1024, 2048$ and $4096$ } 
    	\label{MF_PL_err}
    \end{figure}
    
     Once the most likely network has been identified through the decimation procedure, we perform the same analysis displayed in Fig  \ref{Jor1_dec}  for ordered and then quenched disordered real-valued couplings
and in Fig  \ref{Jor3_dec} for  complex-valued ordered couplings   In comparison to the results shown in Sec  \ref{sec:res_reg},
  the PLM with decimation leads to rather cleaner results  In Figs  \ref{MF_PL_err} and \ref{MF_PL_TP} we compare the performances of the PLM with decimation in respect to ones of the PLM with $l_2$-regularization  These two techniques are also analysed in respect to a mean-field technique previously implemented on the same XY systems\cite{Tyagi15} 
  
    For what concerns the network of connecting links, in Fig  \ref{MF_PL_TP} we compare the TP curves obtained with the three techniques  The results refer to the case of ordered and real valued couplings, but similar behaviours were obtained for the other cases analysed  
  The four graphs are related to different sample sizes, with $M$ increasing clockwise  When $M$ is high enough, all techniques reproduce the true network  
  However, for lower values of $M$ the performances of the PLM with $l_2$ regularization and with decimation drastically overcome those ones of the previous mean field technique  
  In particular, for $M=256$ the PLM techniques still reproduce the original network while the mean-field method fails to find more than half of the couplings  
  When $M=128$, the network is clearly reconstructed only through the PLM with decimation while the PLM with $l_2$ regularization underestimates the couplings  
  Furthermore, we notice that the PLM method with decimation is able to clearly infer the network of interaction even when $M=N$ signalling that it could be considered also in the under-sampling regime $M<N$   
 
 
In Fig  \ref{MF_PL_err} we compare the temperature behaviour of the reconstruction error 
In can be observed that for all temperatures and for all sample sizes  the reconstruction error, ${\rm err_J}$, (plotted here in log-scale) obtained with the PLM+decimation is always smaller than 
that one obtained with the other techniques  The temperature behaviour of ${\rm err_J}$ agrees with the one already observed for Ising spins in \cite{Nguyen12b} and for XY spins  in \cite{Tyagi15} with a mean-field approach:  ${\rm err_J}$ displays a minimum around $T\simeq 1$ and then it increases for very lower $T$; however,
 the error obtained with the PLM with decimation is several times smaller  than the error estimated by the other methods 



 
 

     
     \section{Conclusions}
     \label{sec:conc}


Different statistical inference methods have been applied to the inverse problem of the XY model 
After a short review of techniques based on pseudo-likelihood and their formal generalization to the model we have tested their performances against data generated by means of Monte Carlo numerical simulations of known instances
with diluted, sparse, interactions 

The main outcome is that the best performances are obtained by means of the  pseudo-likelihood method combined with decimation  Putting to zero (i e , decimating) very weak bonds, this technique turns out to be very precise for  problems whose real underlying interaction network is sparse, i e , the number of couplings per variable does not scale with number of variables 
The PLM + decimation method is compared to the PLM + regularization method, with $\ell_2$ regularization and to a mean-field-based method  The behavior of the quality of the network reconstruction is analyzed by looking at the overall sorted couplings and at the single site couplings, comparing them with the real network, and at the true positive curves in all three approaches  In the PLM +decimation method, moreover, the identification of the number of decimated bonds at which the tilted pseudo-likelihood is maximum allows for a precise estimate of the total number of bonds  Concerning this technique, it is also shown that the network with the most likely number of bonds is also the one of least reconstruction error, where not only the prediction of the presence of a bond is estimated but also its value 

The behavior of the inference quality in temperature and in the size of data samples is also investigated, basically confirming the low $T$ behavior hinted by Nguyen and Berg \cite{Nguyen12b} for the Ising model  In temperature, in particular, the reconstruction error curve displays a minimum at a low temperature, close to the critical point in those cases in which a critical behavior occurs, and a sharp increase as temperature goes to zero  The decimation method, once again, appears to enhance this minimum of the reconstruction error of almost an order of magnitude with respect to other methods 
 
The techniques displayed and the results obtained in this work can be of use in any of the many systems whose theoretical representation is given by Eq  \eqref{eq:HXY} or Eq  \eqref{eq:h_im}, some of which are recalled in Sec  \ref{sec:model}  In particular, a possible application can be the field of light waves propagation through random media and the corresponding problem of the  reconstruction of an object seen through an opaque medium or a disordered optical fiber \cite{Vellekoop07,Vellekoop08a,Vellekoop08b, Popoff10a,Akbulut11,Popoff11,Yilmaz13,Riboli14} 

 	
Context 3: \section{Introduction}
Underwater robot picking is to use the robot to automatically capture sea creatures like holothurian, echinus, scallop, or starfish in an open-sea farm where underwater object detection is the key technology for locating creatures  Until now, the datasets used in this community are released by the Underwater Robot Professional Contest (URPC$\protect\footnote{Underwater Robot Professional Contest: {\bf http://en cnurpc org} }$) beginning from 2017, in which URPC2017 and URPC2018 are most often used for research  Unfortunately, as the information listed in Table \ref{Info}, URPC series datasets do not provide the annotation file of the test set and cannot be downloaded after the contest  
Therefore, researchers \cite{2020arXiv200511552C,2019arXiv191103029L} first have to divide the training data into two subsets, including a new subset of training data and a new subset of testing data, and then train their proposed method and other \emph{SOTA} methods  On the one hand, training other methods results in a significant increase in workload  On the other hand, different researchers divide different datasets in different ways, 
\begin{table}[t]
\renewcommand\tabcolsep{3 5pt}
\caption{Information about all the collected datasets  * denotes the test set's annotations are not available  \emph{3} in Class means three types of creatures are labeled, \emph{i e ,} holothurian, echinus, and scallop  \emph{4} means four types of creatures are labeled (starfish added)  Retention represents the proportion of images that retain after similar images have been removed }
\centering 
\begin{tabular}{|l|c|c|c|c|c|}
\hline
Dataset&Train&Test&Class&Retention&Year \\ 
\hline 
URPC2017&17,655&985*&3&15\%&2017 \\
\hline
URPC2018&2,901&800*&4&99\%&2018 \\
\hline
URPC2019&4,757&1,029*&4&86\%&2019 \\
\hline
URPC2020$_{ZJ}$&5,543&2,000*&4&82\%&2020 \\
\hline
URPC2020$_{DL}$&6,575&2,400*&4&80\%&2020 \\
\hline
UDD&1,827&400&3&84\%&2020 \\
\hline 

\end{tabular}
\label{Info}
\end{table}
\begin{figure*}[htbp]
\begin{center}
\includegraphics[width=1\linewidth]{example pdf}
\end{center}
   \caption{Examples in DUO, which show a variety of scenarios in underwater environments }
\label{exam}
\end{figure*}
causing there is no unified benchmark to compare the performance of different algorithms 
In terms of the content of the dataset images, there are a large number of similar or duplicate images in the URPC datasets  URPC2017 only retains 15\% images after removing similar images compared to other datasets  Thus the detector trained on URPC2017 is easy to overfit and cannot reflect the real performance 
For other URPC datasets, the latter also includes images from the former, \emph{e g }, URPC2019 adds 2,000 new images compared to URPC2018; compared with URPC2019, URPC2020$_{ZJ}$ adds 800 new images  The URPC2020$_{DL}$ adds 1,000 new images compared to the URPC2020$_{ZJ}$  It is worth mentioning that the annotation of all datasets is incomplete; some datasets lack the starfish labels and it is easy to find error or missing labels  \cite{DBLP:conf/iclr/ZhangBHRV17} pointed out that although the CNN model has a strong fitting ability for any dataset, the existence of dirty data will significantly weaken its robustness 
Therefore, a reasonable dataset (containing a small number of similar images as well as an accurate annotation) and a corresponding recognized benchmark are urgently needed to promote community development 


To address these issues, we introduce a dataset called Detecting Underwater Objects (DUO) by collecting and re-annotating all the available underwater datasets  It contains 7,782 underwater images after deleting overly similar images and has a more accurate annotation with four types of classes (\emph{i e ,} holothurian, echinus, scallop, and starfish)  
Besides, based on the MMDetection$\protect\footnote{MMDetection is an open source object detection toolbox based on PyTorch  {\bf https://github com/open-mmlab/mmdetection}}$ \cite{chen2019mmdetection} framework, we also provide a \emph{SOTA} detector benchmark containing efficiency and accuracy indicators, providing a reference for both academic research and industrial applications  It is worth noting that JETSON AGX XAVIER$\protect\footnote{JETSON AGX XAVIER is an embedded development board produced by NVIDIA which could be deployed in an underwater robot  Please refer {\bf https://developer nvidia com/embedded/jetson-agx-xavier-developer-kit} for more information }$ was used to assess all the detectors in the efficiency test in order to simulate robot-embedded environment  DUO will be released in https://github com/chongweiliu soon 

In summary, the contributions of this paper can be listed as follows 

  $\bullet$ By collecting and re-annotating all relevant datasets, we introduce a dataset called DUO with more reasonable annotations as well as a variety of underwater scenes 

  $\bullet$ We provide a corresponding benchmark of \emph{SOTA} detectors on DUO including efficiency and accuracy indicators which could be a reference for both academic research and industrial applications  


\pagestyle{empty}
\section{Background}
In the year of 2017, underwater object detection for open-sea farming is first proposed in the target recognition track of Underwater Robot Picking Contest 2017$\protect\footnote{From 2020, the name has been changed into Underwater Robot Professional Contest which is also short for URPC }$ (URPC2017) which aims to promote the development of theory, technology, and industry of the underwater agile robot and fill the blank of the grabbing task of the underwater agile robot  The competition sets up a target recognition track, a fixed-point grasping track, and an autonomous grasping track  The target recognition track concentrates on finding the {\bf high accuracy and efficiency} algorithm which could be used in an underwater robot for automatically grasping 

The datasets we used to generate the DUO are listed below  The detailed information has been shown in Table \ref{Info} 

  {\bf URPC2017}: It contains 17,655 images for training and 985 images for testing and the resolution of all the images is 720$\times$405  All the images are taken from 6 videos at an interval of 10 frames  However, all the videos were filmed in an artificial simulated environment and pictures from the same video look almost identical  
  
   {\bf URPC2018}: It contains 2,901 images for training and 800 images for testing and the resolutions of the images are 586$\times$480, 704$\times$576, 720$\times$405, and 1,920$\times$1,080  The test set's annotations are not available  Besides, some images were also collected from an artificial underwater environment 
  
  {\bf URPC2019}: It contains 4,757 images for training and 1029 images for testing and the highest resolution of the images is 3,840$\times$2,160 captured by a GOPro camera  The test set's annotations are also not available and it contains images from the former contests 
  
  {\bf URPC2020$_{ZJ}$}: From 2020, the URPC will be held twice a year  It was held first in Zhanjiang, China, in April and then in Dalian, China, in August  URPC2020$_{ZJ}$ means the dataset released in the first URPC2020 and URPC2020$_{DL}$ means the dataset released in the second URPC2020  This dataset contains 5,543 images for training and 2,000 images for testing and the highest resolution of the images is 3,840$\times$2,160  The test set's annotations are also not available 
  
  {\bf URPC2020$_{DL}$}: This dataset contains 6,575 images for training and 2,400 images for testing and the highest resolution of the images is 3,840$\times$2,160  The test set's annotations are also not available 
  
  {\bf UDD \cite{2020arXiv200301446W}}: This dataset contains 1,827 images for training and 400 images for testing and the highest resolution of the images is 3,840$\times$2,160  All the images are captured by a diver and a robot in a real open-sea farm 

\begin{figure}[t]
\begin{center}
\includegraphics[width=1\linewidth]{pie pdf}
\end{center}
   \caption{The proportion distribution of the objects in DUO }
\label{pie}
\end{figure}



\begin{figure*}
  \centering
  \subfigure[]{\includegraphics[width=3 45in]{imagesize pdf}}
  \subfigure[]{\includegraphics[width=3 45in]{numInstance pdf}}
  \caption{(a) The distribution of instance sizes for DUO; (b) The number of categories per image }
  \label{sum}
\end{figure*}
\section{Proposed Dataset}

\subsection{Image Deduplicating}
As we explained in Section 1, there are a large number of similar or repeated images in the series of URPC datasets  Therefore, it is important to delete duplicate or overly similar images and keep a variety of underwater scenarios when we merge these datasets together  Here we employ the Perceptual Hash algorithm (PHash) to remove those images  PHash has the special property that the hash value is dependent on the image content, and it remains approximately the same if the content is not significantly modified  Thus we can easily distinguish different scenarios and delete duplicate images within one scenario  

After deduplicating, we obtain 7,782 images (6,671 images for training; 1,111 for testing)  The retention rate of the new dataset is 95\%, which means that there are only a few similar images in the new dataset  Figure \ref{exam} shows that our dataset also retains various underwater scenes 

\subsection{Image Re-annotation}
Due to the small size of objects and the blur underwater environment, there are always missing or wrong labels in the existing annotation files  In addition, some test sets' annotation files are not available and some datasets do not have the starfish annotation  In order to address these issues, we follow the next process which combines a CNN model and manual annotation to re-annotate these images  Specifically, we first train a detector (\emph{i e ,} GFL \cite{li2020generalized}) with the originally labeled images  After that, the trained detector predicts all the 7,782 images  We treat the prediction as the groundtruth and use it to train the GFL again  We get the final GFL prediction called {\bf the coarse annotation}  Next, we use manual correction to get the final annotation called {\bf the fine annotation}  Notably, we adopt the COCO \cite{Belongie2014} annotation form as the final format 
\subsection{Dataset Statistics}
{\bf The proportion of classes}: The total number of objects is 74,515  Holothurian, echinus, scallop, and starfish are 7,887, 50,156, 1,924, and 14,548, respectively  Figure \ref{pie} shows the proportion of each creatures where echinus accounts for 67 3\% of the total  The whole data distribution shows an obvious long-tail distribution because the different economic benefits of different seafoods determine the different breed quantities 

{\bf The distribution of instance sizes}: Figure \ref{sum}(a) shows an instance size distribution of DUO  \emph{Percent of image size} represents the ratio of object area to image area, and \emph{Percent of instance} represents the ratio of the corresponding number of objects to the total number of objects  Because of these small creatures and high-resolution images, the vast majority of objects occupy 0 3\% to 1 5\% of the image area 

{\bf The instance number per image}: Figure \ref{sum}(b) illustrates the number of categories per image for DUO  \emph{Number of instances} represents the number of objects one image has, and \emph{ Percentage of images} represents the ratio of the corresponding number of images to the total number of images  Most images contain between 5 and 15 instances, with an average of 9 57 instances per image 

{\bf Summary}:
In general, smaller objects are harder to detect  For PASCAL VOC \cite{Everingham2007The} or COCO \cite{Belongie2014}, roughly 50\% of all objects occupy no more than 10\% of the image itself, and others evenly occupy from 10\% to 100\%  
In the aspect of instances number per image, COCO contains 7 7 instances per image and VOC contains 3  In comparison, DUO has 9 57 instances per image and most instances less than 1 5\% of the image size 
Therefore, DUO contains almost exclusively massive small instances and has the long-tail distribution at the same time, which means it is promising to design a detector to deal with massive small objects and stay high efficiency at the same time for underwater robot picking 

\section{Benchmark}
Because the aim of underwater object detection for robot picking is to find {\bf the high accuracy and efficiency} algorithm, we consider both the accuracy and efficiency evaluations in the benchmark as shown in Table \ref{ben} 

\subsection{Evaluation Metrics}
Here we adopt the standard COCO metrics (mean average precision, \emph{i e ,} mAP) for the accuracy evaluation and also provide the mAP of each class due to the long-tail distribution 

{\bf AP} -- mAP at IoU=0 50:0 05:0 95 

{\bf AP$_{50}$} --  mAP at IoU=0 50 

{\bf AP$_{75}$} --  mAP at IoU=0 75  

{\bf AP$_{S}$} --   {\bf AP} for small objects of area smaller than 32$^{2}$ 

{\bf AP$_{M}$} --   {\bf AP} for objects of area between 32$^{2}$ and 96$^{2}$ 

{\bf AP$_{L}$} --   {\bf AP} for large objects of area bigger than 96$^{2}$ 

{\bf AP$_{Ho}$} --  {\bf AP} in holothurian 

{\bf AP$_{Ec}$} --  {\bf AP} in echinus 

{\bf AP$_{Sc}$} --  {\bf AP} in scallop 

{\bf AP$_{St}$} --  {\bf AP} in starfish 


For the efficiency evaluation, we provide three metrics:

{\bf Param } --  The parameters of a detector 

{\bf FLOPs} --  Floating-point operations per second 

{\bf FPS} --  Frames per second 

Notably, {\bf FLOPs} is calculated under the 512$\times$512 input image size and {\bf FPS} is tested on a JETSON AGX XAVIER under MODE$\_$30W$\_$ALL  

\subsection{Standard Training Configuration}
We follow a widely used open-source toolbox, \emph{i e ,} MMDetection (V2 5 0) to produce up our benchmark  During the training, the standard configurations are as follows:

  $\bullet$ We initialize the backbone models (\emph{e g ,} ResNet50) with pre-trained parameters on ImageNet \cite{Deng2009ImageNet} 

  $\bullet$ We resize each image into 512 $\times$ 512 pixels both in training and testing  Each image is flipped horizontally with 0 5 probability during training 

  $\bullet$ We normalize RGB channels by subtracting 123 675, 116 28, 103 53 and dividing by 58 395, 57 12, 57 375, respectively 

  $\bullet$ SGD method is adopted to optimize the model  The initial learning rate is set to be 0 005 in a single GTX 1080Ti with batchsize 4 and is decreased by 0 1 at the 8th and 11th epoch, respectively  WarmUp \cite{2019arXiv190307071L} is also employed in the first 500 iterations  Totally there are 12 training epochs 

  $\bullet$ Testing time augmentation (\emph{i e ,} flipping test or multi-scale testing) is not employed 



\subsection{Benchmark Analysis}
Table \ref{ben} shows the benchmark for the \emph{SOTA} methods  Multi- and one- stage detectors with three kinds of backbones (\emph{i e ,} ResNet18, 50, 101) give a comprehensive assessment on DUO  We also deploy all the methods to AGX to assess efficiency 

In general, the multi-stage (Cascade R-CNN) detectors have high accuracy and low efficiency, while the one-stage (RetinaNet) detectors have low accuracy and high efficiency  However, due to recent studies \cite{zhang2019bridging} on the allocation of more reasonable positive and negative samples in training, one-stage detectors (ATSS or GFL) can achieve both high accuracy and high efficiency 

\begin{table*}[htbp]
\renewcommand\tabcolsep{3 0pt}

\begin{center}
\caption{Benchmark of \emph{SOTA} detectors (single-model and single-scale results) on DUO  FPS is measured on the same machine with a JETSON AGX XAVIER under the same MMDetection framework, using a batch size of 1 whenever possible  R: ResNet } 
\label{ben}
\begin{tabular}{|l|l|c|c|c|ccc|ccc|cccc|}
\hline
Method&Backbone&Param &FLOPs&FPS&AP&AP$_{50}$&AP$_{75}$&AP$_{S}$&AP$_{M}$&AP$_{L}$&AP$_{Ho}$&AP$_{Ec}$&AP$_{Sc}$&AP$_{St}$ \\ 
\hline 
\emph{multi-stage:} &&&&&&&&&&&&&& \\

\multirow{3}{*}{Faster R-CNN \cite{Ren2015Faster}}
&R-18&28 14M&49 75G&5 7&50 1&72 6&57 8&42 9&51 9&48 7&49 1&60 1&31 6&59 7\\
&R-50&41 14M&63 26G&4 7&54 8&75 9&63 1&53 0&56 2&53 8&55 5&62 4&38 7&62 5\\
&R-101&60 13M&82 74G&3 7&53 8&75 4&61 6&39 0&55 2&52 8&54 3&62 0&38 5&60 4\\
\hline

\multirow{3}{*}{Cascade R-CNN \cite{Cai_2019}}
&R-18&55 93M&77 54G&3 4&52 7&73 4&60 3&\bf 49 0&54 7&50 9&51 4&62 3&34 9&62 3\\
&R-50&68 94M&91 06G&3 0&55 6&75 5&63 8&44 9&57 4&54 4&56 8&63 6&38 7&63 5\\
&R-101&87 93M&110 53G&2 6&56 0&76 1&63 6&51 2&57 5&54 7&56 2&63 9&41 3&62 6\\
\hline

\multirow{3}{*}{Grid R-CNN \cite{lu2019grid}}
&R-18&51 24M&163 15G&3 9&51 9&72 1&59 2&40 4&54 2&50 1&50 7&61 8&33 3&61 9\\
&R-50&64 24M&176 67G&3 4&55 9&75 8&64 3&40 9&57 5&54 8&56 7&62 9&39 5&64 4\\
&R-101&83 24M&196 14G&2 8&55 6&75 6&62 9&45 6&57 1&54 5&55 5&62 9&41 0&62 9\\
\hline

\multirow{3}{*}{RepPoints \cite{yang2019reppoints}}
&R-18&20 11M&\bf 35 60G&5 6&51 7&76 9&57 8&43 8&54 0&49 7&50 8&63 3&33 6&59 2\\
&R-50&36 60M&48 54G&4 8&56 0&80 2&63 1&40 8&58 5&53 7&56 7&65 7&39 3&62 3\\
&R-101&55 60M&68 02G&3 8&55 4&79 0&62 6&42 2&57 3&53 9&56 0&65 8&39 0&60 9\\
\hline 
\hline 
\emph{one-stage:} &&&&&&&&&&&&&& \\
\multirow{3}{*}{RetinaNet \cite{Lin2017Focal}}
&R-18&19 68M&39 68G&7 1&44 7&66 3&50 7&29 3&47 6&42 5&46 9&54 2&23 9&53 8\\
&R-50&36 17M&52 62G&5 9&49 3&70 3&55 4&36 5&51 9&47 6&54 4&56 6&27 8&58 3\\
&R-101&55 16M&72 10G&4 5&50 4&71 7&57 3&34 6&52 8&49 0&54 6&57 0&33 7&56 3\\
\hline 

\multirow{3}{*}{FreeAnchor \cite{2019arXiv190902466Z}}
&R-18&19 68M&39 68G&6 8&49 0&71 9&55 3&38 6&51 7&46 7&47 2&62 8&28 6&57 6\\
&R-50&36 17M&52 62G&5 8&54 4&76 6&62 5&38 1&55 7&53 4&55 3&65 2&35 3&61 8\\
&R-101&55 16M&72 10G&4 4&54 6&76 9&62 9&36 5&56 5&52 9&54 0&65 1&38 4&60 7\\
\hline 

\multirow{3}{*}{FoveaBox \cite{DBLP:journals/corr/abs-1904-03797}}
&R-18&21 20M&44 75G&6 7&51 6&74 9&57 4&40 0&53 6&49 8&51 0&61 9&34 6&59 1\\
&R-50&37 69M&57 69G&5 5&55 3&77 8&62 3&44 7&57 4&53 4&57 9&64 2&36 4&62 8\\
&R-101&56 68M&77 16G&4 2&54 7&77 3&62 3&37 7&57 1&52 4&55 3&63 6&38 9&60 8\\
\hline 

\multirow{3}{*}{PAA \cite{2020arXiv200708103K}}
&R-18&\bf 18 94M&38 84G&3 0&52 6&75 3&58 8&41 3&55 1&50 2&49 9&64 6&35 6&60 5\\
&R-50&31 89M&51 55G&2 9&56 8&79 0&63 8&38 9&58 9&54 9&56 5&66 9&39 9&64 0\\
&R-101&50 89M&71 03G&2 4&56 5&78 5&63 7&40 9&58 7&54 5&55 8&66 5&42 0&61 6\\
\hline 

\multirow{3}{*}{FSAF \cite{zhu2019feature}}
&R-18&19 53M&38 88G&\bf 7 4&49 6&74 3&55 1&43 4&51 8&47 5&45 5&63 5&30 3&58 9\\
&R-50&36 02M&51 82G&6 0&54 9&79 3&62 1&46 2&56 7&53 3&53 7&66 4&36 8&62 5\\
&R-101&55 01M&55 01G&4 5&54 6&78 7&61 9&46 0&57 1&52 2&53 0&66 3&38 2&61 1\\
\hline 

\multirow{3}{*}{FCOS \cite{DBLP:journals/corr/abs-1904-01355}}
&R-18&\bf 18 94M&38 84G&6 5&48 4&72 8&53 7&30 7&50 9&46 3&46 5&61 5&29 1&56 6\\
&R-50&31 84M&50 34G&5 4&53 0&77 1&59 9&39 7&55 6&50 5&52 3&64 5&35 2&60 0\\
&R-101&50 78M&69 81G&4 2&53 2&77 3&60 1&43 4&55 4&51 2&51 7&64 1&38 5&58 5\\
\hline 

\multirow{3}{*}{ATSS \cite{zhang2019bridging}}
&R-18&\bf 18 94M&38 84G&6 0&54 0&76 5&60 9&44 1&56 6&51 4&52 6&65 5&35 8&61 9\\
&R-50&31 89M&51 55G&5 2&58 2&\bf 80 1&66 5&43 9&60 6&55 9&\bf 58 6&67 6&41 8&64 6\\
&R-101&50 89M&71 03G&3 8&57 6&79 4&65 3&46 5&60 3&55 0&57 7&67 2&42 6&62 9\\
\hline 

\multirow{3}{*}{GFL \cite{li2020generalized}}
&R-18&19 09M&39 63G&6 3&54 4&75 5&61 9&35 0&57 1&51 8&51 8&66 9&36 5&62 5\\
&R-50&32 04M&52 35G&5 5&\bf 58 6&79 3&\bf 66 7&46 5&\bf 61 6&55 6&\bf 58 6&\bf 69 1&41 3&\bf 65 3\\
&R-101&51 03M&71 82G&4 1&58 3&79 3&65 5&45 1&60 5&\bf 56 3&57 0&\bf 69 1&\bf 43 0&64 0\\


\hline 
\end{tabular}
\end{center}
\end{table*}
Therefore, in terms of accuracy, the accuracy difference between the multi- and the one- stage methods in AP is not obvious, and the AP$_{S}$ of different methods is always the lowest among the three size AP  For class AP, AP$_{Sc}$ lags significantly behind the other three classes because it has the smallest number of instances  In terms of efficiency, large parameters and FLOPs result in low FPS on AGX, with a maximum FPS of 7 4, which is hardly deployable on underwater robot  Finally, we also found that ResNet101 was not significantly improved over ResNet50, which means that a very deep network may not be useful for detecting small creatures in underwater scenarios  

Consequently, the design of high accuracy and high efficiency detector is still the main direction in this field and there is still large space to improve the performance 
In order to achieve this goal, a shallow backbone with strong multi-scale feature fusion ability can be proposed to extract the discriminant features of small scale aquatic organisms; a specially designed training strategy may overcome the DUO's long-tail distribution, such as a more reasonable positive/negative label sampling mechanism or a class-balanced image allocation strategy within a training batch 

\section{Conclusion}
In this paper, we introduce a dataset (DUO) and a corresponding benchmark to fill in the gaps in the community  DUO contains a variety of underwater scenes and more reasonable annotations  Benchmark includes efficiency and accuracy indicators to conduct a comprehensive evaluation of the \emph{SOTA} decoders  The two contributions could serve as a reference for academic research and industrial applications, as well as promote community development 



ground_truth: It outperforms mean-field methods and the PLM with $l_2$ regularization in terms of reconstruction error and true positive rate.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: Does DUO contain more instances per image than COCO?

Read the following text and answer briefly.

Context 4:  The best performing model checkpoint was chosen according to the epoch-wise validation macro-F1 score  5 Experiments and Results

Experiments using Large Language Models

For the task of Dialect Identification we have tried various language specific models like XLM-RoBERTa, BERT, ELECTRA, RoBERTa and GPT- 2  The base variant of all these models were used and all the models were used through the Hugging-Face library  The pooler output of these models was passed through a linear layer and the models were fine-tuned 
First, we experimented with different models for Track-1  All the models were trained for 20 epochs with learning rate 1e-6, weight decay 1e-6 and a batch size of 8  We used XLM-RoBERTa as the baseline for all 3 languages  The best performing models for the English language were RoBERTa and BERT whereas GPT-2 was the worst performing 
Similarly the language specific versions of RoBERTa and BERT performed well for the Spanish and Portuguese respectively  Overall the worst performing model was GPT-2 across all 3 languages  The validation F1 scores are present in Table   The two best-performing models for every language were chosen for Track-2 
The same procedure as specified above was used and the F1 scores are present in Table   The train and validation F1 scores for 2-class classification are higher for all models as compared to the F1 score of the same models for 3-class classification  This was mainly due to the poor representation and accuracy of classification of the third class 
We observed symptoms of overfitting in all models after 12-15 epochs and the best validation F1 score was obtained in the range of 4-8 epochs 

LID experiments

The pipeline for dialect identification is divided into two parts as the sentences in the dataset belong to different languages  The stages are described in Section 4  The XLM-RoBERTa we have used for language classification has a test accuracy of 99 6% meaning it correctly classifies all input sentences and hence, can be considered as a perfect classifier 
For the final pipeline we experimented using the two best performing models for each language in Track-1 and Track-2  For both the tracks we experimented with all 8 (2 3 ) possible combinations of models and calculated the validation F1 score for the combined validation dataset which had sentences belonging to all languages 
The validation scores for Track-1 and Track-2 are shown in Table and Table respectively  For both the tracks, the three pipelines with the best validation F1 scores were chosen for submission 

Using 3-way classifier as a 2-way classifier

In Track-1, participants are expected to train a classifier which classifies amongst 9 classes, and in Track-2, participants are expected to train a classifier which classifies amongst 6 classes  These 6 classes are a proper subset of the 9 classes from Track-1  Thus, an intuitive baseline for Track-2 is to use the model finetuned for Track-1, whilst considering only the relevant classes for the latter task 
The classes EN , ES and P T , i e  the classes without any national dialect associated with them are not included in Track-2 as compared to Track-1  Thus, we calculate the predictions for the Track-2 validation dataset using the models for Track-1 and exclude the metrics for Track-1 specific classes to get the metrics for this "adapted" 2-way classification 
We show the results of this experiment in Table and observe that, as expected, the adapted 2-way classification performs worse compared to the explicitly finetuned variant 

Results for Track-1 and Track-2

We now present our experiments and their performance for both tracks  Our experiments for Track-1 are described in Table and our experiments for Track-2 are described in Table   The participants were allowed three submissions for evaluation on the test set, so we submitted predictions using the three systems which performed the best on the validation set 
As mentioned in Section 5 2, we performed 2 3 , i e  a total of 8 experiments using the two best models for each language  We observed that RoBERTa base on English, Spanish BERT base on Spanish and Portuguese BERT base performed the best on the testing set for Track-1  The same combination, with RoBERTa base for English, worked best for Track-2 
All of our submissions were the top submissions for each track, which surpassed the next best competitors by a margin of 4 5% and 5 6% for Track-1 and Track-2 respectively 

Ablation of best submissions

We hereby make some observations of our submissions and other experiments  To assist this, we plot the confusion matrices of our best submissions for Track-1 and Track-2 in Figures respectively  Note that these confusion matrices have their rows (i e  true labels axes) normalized according to the number of samples in the class 
Here are observations from our experiments: 1  BERT-based models outperform other models across all languages: We observe that BERT-based models outperform ELECTRA-based and GPT-2-based models, as shown in Table   We speculate this is because of the inherent architecture of BERT, which combines semantic learning with knowledge retention 
This combination of traits is particularly useful for this task  2  Common labels perform the worst across all languages: We observe that the common labels EN , ES and P T perform the worst, both in the individual as well as the two-stage setup  We hypothesize this is because of the absence of dialect specific words, or words that are specific to the geographical origin of the national dialect (for example, "Yankees" for EN-US and "Oxford" for EN-GB) 
3  English models work better than models of other languages: It can be noted from Figures 4 and 3 that the English models have the best performance across all classes  This can be attributed to two reasons: absence of national dialect specific words and lesser pretraining data in the case of Portuguese 
4  British English is most correctly classified class: We can observe that the Spanish or Portuguese models make equal number of mistakes in the case of either national dialect, in the case of Track-2 (see Figure )  However, in the case of English, the label EN − GB is correctly classified for more than 95% of the cases 
We speculate this is because British English involves slightly distinctive grammar and semantics, which help the model separate it from other classes  5  The proposed 2-step method is scalable for multiple language dialect classification: We can strongly assert that the novel 2-step deep learning method for multilingual dialect classification is a scalable method for the task due to two specific reasons: firstly, the multilingual models (like XLM-RoBERTa) might not have the vocabulary as well as the learning capabilities to learn the minute differences between individual dialects 
Secondly, this system can be quickly expanded for a new language by simply adding a language specific dialect classifier, provided the language identification model supports that particular language 

Conclusion

In this paper we propose a two-stage classification pipeline for dialect identification for multilingual corpora  We conduct thorough ablations on this setup and provide valuable insights  We foresee multiple future directions for this work  The first is to expand this work to many languages and dialects 
Secondly, it is a worthwhile research direction to distill this multi-model setup into a single model with multiple prediction heads  The obvious limitation of this system is the excessive memory consumption due to the usage of language specific models  For low resource languages this system is difficult to train and scale 
We hope that these problems will be addressed by researchers in future works 



ground_truth: Yes, DUO has 9.57 instances per image while COCO contains 7.7.