skysight-inc/HackerNews huggingface dataset:
In the context of linear regression, there is no particular reason to assume noise is i.i.d. and Gaussian. The former is part of the the Gauss-Markov conditions, under which OLS is BLUE (the "best linear unbiased estimator"). The latter is not necessary at all. And of the Gauss-Markov conditions can be violated to varying degrees of consequence.

In fact, in real data, these assumptions are almost always violated. The Gaussian assumption doesn't matter at all, but to address the i.i.d. assumption: Almost all real data exhibits residual heteroskedasticity and almost all real data has observable clustering. Which is why almost no one uses OLS with classical errors. We have estimators to allow errors to be heteroskedasticity-consistent (the default in STATA and easily estimated in R e.g. by estimatr, clubSandwich, etc) or cluster-robust or both. By definition these cases have non-i.i.d. errors and there's no reason linear regression can't be used with them.

We also don't need to make assumptions, these can be interrogated. Most regression relies on using the residual matrix as sample plug-ins for the underlying error matrix, so there's a wide assortment of diagnostic techniques to check for the presence or absence of those assumptions.

Insofar as "machine learning" has any meaning -- which is to say, insofar as it is different than "statistics", the difference is purportedly that it focuses on minimizing out of sample prediction error rather than estimating population parameters, and typically this is motivated as an overfitting problem.

We use OLS because OLS is BLUE under the Gauss-Markov conditions. In ML we rarely care about "U" (unbiasedness) because we frequently prefer to make a bias-variance tradeoff if we're aiming to minimize out of sample error. When linear regression is used in an ML context it is typically penalized linear regression (i.e. ridge / LASSO). Of course it's also the case that the bulk of sexy ML results come out of non-linear estimators, and absent a need to characterize population parameters there's no real reason to care about interpretability so really we don't care about the "L" either.

I would say the grandparent is closer to right. Often in ML there is a view that we throw a bunch of processes at data, pick the thing that works best, don't care why it works at all, and then run with it. To the extent there's a protection against fishing expeditions, it's in the training/test separation or cross-validation or both.

Most of the time when someone talks about "regression theory", they're used 30 or 40 year old results. For an updated look, check out "Foundations of Agnostic Regression" (Aronow and Miller, both Yale Political Scientists) which is coming out some time in 2019. They've had a pre-print around for a while and if you're interested I'm sure you could get one.
Don't care one bit about this. Whatsoever.
China have introduce very strict rules for NGO last year: http://www.chinafile.com/ngo/latest/fact-sheet-chinas-foreig...

Basically, a foreign NGO need to register with the government to continue their work in China.

Some of the NGO is still working on getting the approval. These two Canadians were working with one of those NGO.
I was about to report the same personal experience, so that's twice the amount of anecdotal evidence in favor of the environment/habits and against inner causes.
That's a shockingly terrible argument. A person can object to parts of a service while still wanting to purchase the service.

If only the world was so simple.
What constitutes an "extraordinary" level in "extraordinary claims" is one the least-defined things in aphorisms related to science. It reminds me of what some call the "stages of change" First, it is ridiculed. Second, it is violently opposed. Third, it is accepted as being self-evident.

It seems if what is "extraordinarily" unlikely can easily become "true and self-evident" then extraordinary was a more a way of fighting against things opposed for more emotional than evidentiary reasons.
Stop playing the victim.

Just make a driverless car that never makes mistakes already -- and I promise you the goalpost won't move for a while.

Go and chess mean nothing out there. The world has a lot of very practical and concrete needs that this magical "AI" is nowhere near solving yet.

I find the constant defensiveness of the ML proponents tiring and cringe-worthy. Somebody should remind you that what you are doing is not a backyard hobby. The people who fund you make a lot of promises and I don't think any of them have been delivered.
My guess is that most people feel AI should be held to a higher standard is because we feel the need to be able to audit the system in the case of mishaps. When ML becomes a high-level black box, we may not have the confidence in how to right that ship if it goes astray. With human errors, if we're (hopefully) empathetic creatures we at least have the hope of understanding the root of the error.
China used to heavily depend on outsourcing perhaps a decade ago; there's been a marked shift to serving their own audience and building for that marketplace.

India still depends heavily on outsourcing.

It's rather expensive to look at Chinese outsourcing currently, India is still relatively cheap. Vietnam is the new hotbed of outsourcing.
How did you get into this?
It feels in tone like the "I'll miss VCR" stuff that went around in 2016 all over again. A little over dramatic given the difference.

https://www.wired.com/2016/07/vcr-officially-dead-well-never...
Bigger fish to fry than one of the richest people in China who has (allegedly) been directly involved in transferring the technology? That we can actually get our hands on?

Just looking at how the Chinese government has reacted, I think it's clear that this is a pretty big fish.
Do you have more you can share on this?
>Canada can choose to walk away

What is "walking away" in this context? Releasing Meng, and in the process, reneging on the extradition treaty?
This is how I grew up to hate hockey.
The issue with "unknown unknowns" is that they are uncertainties and not risks. Risks we can more easily deal with because they are quantifiable so they can be hedged against with probabilities.
Complete agreement from me here. I refuse to buy a phone without a headphone jack. It's such a simple thing, but it represents such a middle finger to consumers that it's enough for me to say no.

My iPhone 6s is fine. An older pixel will be fine too as soon as I figure out how to ditch iMessage.

This actually feels a lot like how Facebook seems to intentionally cripple their mobile site to try and get me to install their app so they can have more of my info. It's inconveniencing me very deliberately to try and hold my convenience hostage.
> Oh, wait: now I want to listen to music while I fall asleep, but also charge my phone so it’s not dead in the morning. That’s a different, more expensive splitter dongle (many of which, I’ve found, are poorly made garbage).

Or a wireless charging pad plus regular adapter.

(I'm a fine one to talk; I have an OG Pixel, and I use my headphone jack entirely for the headset functionality when doing a conference call while remote. A sub-$10 wired headset gets the job done... for now)
You can use the stars to set time too: https://www.esa.int/Our_Activities/Navigation/ESA_sets_clock...

To claim that the two radio stations in Colorado and Hawaii are our last grasp on time is a bit of a stretch.

There are legacy systems in existence that rely on those stations, but none really seem particularly critical or that can't be easily moved over to something more modern than church bells.
There were good, ubiquitous replacements for VCRs when DVD players came out.

This would be like if Sony stopped selling VCRs in 1998 when they just happened to own the patent on blu ray, and a major movie studio.

Actually it's exactly what Sony tried to do with minidisc, except it worked.
There is no reason to miss the headphone port unless cost is the main factor.
Amazon Corretto – Free, multiplatform, production-ready distribution of OpenJDK
Show HN: Generate-Resume: Node CLI to Generate Resume in HTML and PDF from XML
Yeah but that wireless charger should be an added convenience, not an anti-user move to get you to buy more crap.

It feels like a recent thing to me, but companies (especially tech companies) have gone from:

"We will make the best product we can, and you will pay us for it."

(Or perhaps some graph where marginal profit is the highest)

To

"We will make the worst product we can get away with making because you don't have a choice."

The focus seems to have gone from what customers want to what customers will tolerate.
No shit. It’s bizarre that I can’t use my headphones and charge at the same time. It’s bizarre that I have to carry around an adapter (or two sets of headphones) when I work because my MacBook and iPhone have different headphone jacks. I’m generally happy with Apple’s products, but this choice leaves me baffled.
I’ve thought for a while now that there is a special depravity to things like littering that makes them worse than, for example, small-time theft.

At least the thief has a rational reason to steal and gains from his crime roughly what he has taken from another. The litterer by comparison gains so little but does so much harm.
When I was a teen, my clock was 27 hours. I did the vacation and natural wakeups and rotated around the clock in 7 days. It's decreased a bit but I think it's still around 25-26 hours.
From James Gosling (creator of Java) himself: https://twitter.com/errcraft/status/1062641930205622273
I'm fortunate to have had parents who let me sleep in on weekends, and I definitely felt like a night owl in my teenage years. Now in my thirties I seem to function best in the morning. Typing this at 7am on boxing day - I've been awake a while already without a reason at all.

Keep in mind that your circadian clock changes with different life stages. Teenagers have been shown to have circadian rhythms that run a few hours later than that of adults.

One example: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2820578/
My experience is exactly the same, I had a lot of different sleeping schedules over the years (usually late to very late). Currently waking up at 6AM is also the new normal for me.

It just can be really hard to change it if you are not forced to do so but after some weeks you adjust. It's especially difficult to switch from late to early in my experience because constantly staying awake longer is easy (especially with all the "modern distractions") but getting out of bed too early is really a pain so you often don't do it if not forced to.
AFIK, everything is going to GPS and ADS-B.
I'm sticking with the 6S myself due to lack of headphone jack. I estimate I'll keep the 6S another 4-5 years as there's longevity in these devices I feel. Not sure what I'd do at that point because I think the iPhone in general is great.
Friendly reminder to go get your battery replaced before the end of the year!
If it happens and doesn’t involve more than the current DL approach.
Vim, preferably Neovim.
Based on the context of the two comments you replied to, my interpretation of “walking away” would be Canada declining to further escalate retribution toward China.

Presumably retribution drags them in on the side of the US, but abstaining pins them between two superpowers.
Ask HN: What’s your plan in 2019?
Learning, startup or anything.
An old-school, pay-for blogging platform in the indieweb vein.
Ditching the headphone port is a great example of the form over function mindset that I find so grating about much of the tech industry. I don't care about flashy or gimmicky changes, I just want things to work and work well.

FWIW, I use the port on my phone regularly and love never having to give it a second thought. Removing the port was the biggest reason I did not replace my old Nexus with a new Pixel. I'm just one person and am guessing the port is doomed sooner rather than later, but at least for now I can put my money where my mouth is.
Afaict that's the paper that says code using GC needs five times as much memory to have performance comparable to manual management.

What's the figure these days?
Many studies have found otherwise.[1] Delayed sleep in adolescence has even been observed in other mammals.

[1] https://en.wikipedia.org/wiki/Chronotype
Do you have any quick references for someone not privy to this state of the art but who has experience reading academic papers and reading code and documentation?
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Big cities aren’t quiet at night
All big countries disregard EU rules. France has been disregarding rules a lot more and never gets punished according to EU law. Small countries in Eastern Europe get picked on for violating the same stuff France / Italy / Germany violate. So that system has no credibility if not all countries are treated equally.

Your point about deficits (Maastricht Treaty and other EU regulations after the crises that passed), everybody ignores that but only small countries every get in trouble for it. And when it comes to deficits, Germany is actually one of lesser offenders compared to others.

Also, it has been known for a long time that an agreement when EU was being formed was made and areas of influence setup. Germany was promised to get leading influence in ECB in exchange for basically turning Deutsche Mark into Euro and allowing the whole continent to use the German currency. French got full control of the IMF, for example, and also EU parliament being located partly in Strasbourg plus more influence in some other core EU bodies outside of ECB.
>It barely learns anything given the amount of computation effort an data that goes into it, but it just happens to be good enough to be practically preferable to old symbolic systems.

This is the part that's always bothered me. For many ML has just become the default tool to throw at a problem where other solutions (albeit less shiny) exist, that might give the same or even better results (and are very likely going to end up being more efficient). Would it be too much of a leap to suggest that we're forgetting to think?
Interesting. You are right not new to China but the IP laws make it harsh.

At the end of the day, it's all code. Not sure I would ever work for a company that makes you work like a sick man just to get even the with the uneven level field.

How hard is it to get into Tencent/Baidu?
When you hire lowest wage coders, bad ones won't care, good ones will jump ship midway or once it's done.
Same on desktop, appears to be a deliberate design choice to make the bottom, non-header, part as an overflow:auto div so it gets it's own scrollbar.
TLDR; Learning to play musical instruments or playing chess does NOT improve IQ. Lively conversation with complex vocabulary, interactive reading with child, memory games and not ending school prematurely helps.
I worked as a Full Stack Developer with BookMyShow in Mumbai, India. We are a ticketing company somewhat like TicketMaster is in the United States.

The company was around 10 years old and transitioning from what one could term as a start up mentality into a full fledged product company.

Methodology: had formally adopted Agile around 2016-2017. A part of this adoption included some formal training by an experienced agile coach.

Code : I can probably speak for the entire country and say code is written in English. Most of the country learns English through highschool if not through kindergarten. Code and CS concepts are learnt in English too. Infact I've never seen code written in any other language.

Languages : Languages popular include but aren't restricted to Java, JavaScript and Python. Although I have observed that Java seems to be more popular or well known than C++.

Tooling: We used a majority of the Atlassian softwares to track the product lifecycle. Additionally we also had Docker, Kubernetes, ELK and Splunk Deployments.

Culture : This is where I'm probably not necessarily the best person to comment with respect to the whole country.

The work I did was valued and we were encouraged to understand why we were doing a particular task. You could discuss/debate over choice of technology or approach with your boss. Teams were empowered to make a majority of decisions.

Friends from fish-tin companies aka the outsourcing companies have drastically different views than mine. Run of the mill work - shitty culture.
>Can anyone point to some unbiased ... sources ...

"No", is the short answer.

You simply have to read the position of all sides, and then make your own decisions. Any source that people will point you to, is going to be biased in some fashion.
This really annoys me. Not the person trying to fill the car, but the giggling idiot who took the video. Ha ha. Why not get out of the car, and tell the person that the car takes no gas. No. Rather ridicule her in front of 2.4M people (and counting). Oh, goody, your social network standing has gone up. Where the explicative has common public decency gone.
Somehow, I expect a crystal radio will survive an EMP that fries every P-N junction in a digital device... That's robust. Crystal radios don't even need batteries.

https://en.wikipedia.org/wiki/Crystal_radio
Aren’t those “people “ the heads of multinational financial institutions like Goldman Sachs?

Almost every EU country has someone from GS in their leadership structure over the years.

They simply engineered an arbitrage situation...
Snowboarding.

There is no snow (or seasons) where I grew up. I first started snowboarding while attending university at the tender age of 27. The combination of multiple factors (foreign introvert with few friends, fewer snowboarding acquaintances, living several hours far from the slopes, cost of gear, bad career moves) stopped me from snowboarding for the next 8 years. Eventually I chanced upon some roommates that go annually, confirming that I do indeed have an innate love for the sport. Now older with a stable income and heck all for others' opinions, I'll go snowboard even just by myself. I actually enjoy snowboarding by myself but the weird thing is this sport has opened me up to more friends, who complain when I don't ask any of them along.

I'll admit that my upbringing has given me a weird fetish for snow and cold weather, but there's just something magical about snowboarding that I can't explain with words.

I'm hoping to hit 50 days on the slopes this year.
the cost of being on the edge of technology is the inconvenience you will encounter.

this "article" (if you can call it that, feels fitting to a blog) doesnt really touch on anything meaningful. The author echos the same tirades that we've seen since the announcement of the iPhone X.
I like to call it 2FA - Fitness, Finance, Autonomy. All my activities will be around these themes, viz. Getting healthier, learning more about personal finance and planning around self-sufficiency in as many aspects of life as possible.
I hate how this is a thing. Mental health be damned. The only way this could be stopped if there was country-wide protests or walk-offs, but I doubt that would ever or could happen.
I’ve been learning Vue myself lately and agree that the documentation is a huge weak point. Even the beginner’s guide leaps around from one advanced concept to another, rather than taking you from step 1 to step 2 to step 3 in easily comprehensible chunks. It makes learning Vue a lot harder than it probably needs to be.
I use Netbeans for C/C++ development (shocking, I know). Originally I was using it as an Eclipse alternative at a Java gig. After moving into embedded dev I just decided to try and stick with it and see how it goes. It worked.

Benefits:

- Free, cross platform. Someday I'll shell out $300 for slick edit, but a free IDE is nice.

- Solid C++/Makefile code analysis. C++ has a notoriously difficult syntax, but Netbeans can handle it.

- support for git and svn to visualize diffs

- very configurable syntax coloring & highlighting, also a good dark theme (Darcula)

- many configurable keybindings

- not vim or emacs ;)

Cons:

- can be a bit heavy/clunky

- there are some quirks that I've learned to work with, perhaps this could be said of any editor...

- on large codebases it will take some time to initially parse everything

- Java font rendering

- looks of disdain and confusion from other engineers

it's probably inertia that's kept me from moving to fancier editors, but overall Netbeans has been solid and I'm just as productive as the other guys & gals.
Cpp-Taskflow Documentation Online: Modern C++ Parallel Task Programming Library
Canada is not stuck in between, they know exactly which side they are on. It's pretty obvious.
have you actually used emacs on a cpu made in the last 20 years and found it to be slow?

Yes. Early 2015 Macbook Pro.
It's hella slow to start up, of course, even on my 2017 mbp. Chugs when scrolling depending on active modes, too.
Machine Learning 101: 2 yrs of headbanging, so you don't have to (2017) [slides]
I agree with your interpretation and pushback against your parent comment, but wanted to elaborate that the "problem" here is much deeper. Deep learning is basically magic, okay, fine, so let's start much closer to linear regression.

Say we have a predictor matrix X with 2 predictors. We fit a model using a penalized linear regression (say LASSO) adding to our predictor matrix an interaction terms, arbitrary polynomial and logarithmic transformations of each X, and interactions between the transformations of the Xes. Ideally we motivate this because of some case knowledge about relevant nonlinear transformations of the predictors. Or maybe second best we use the kernel trick to run a kernelized regression that uses an infinite dimensional prediction of all possible transformations of the predictors. But realistically, we toss some shit in the model and run it.

The LASSO spits out X1, X2^2, and X1^3 * log(X2) as being the cross-validation selected non-zero parameters.

What real world scenario could possibly generate a causal process that is linear in X1 (say income), quadratic in X2 (say age, which often displays quadratic forms in regressions), but also predicted by a bizarre non-linear interaction of nonsense transformations?

What a practitioner would probably do is fit the model. In a lot of ML contexts, interpretation would lead to the practitioner saying "Well, okay, ML sometimes produces nonsense models, but you can't argue with the predictive results". Or maybe the practitioner is more sensitive to interpretability and instead takes another tack. Maybe the practitioner might say "clearly this interaction is nonsense, but there must be some interaction, I'll re-run with a linear interaction". Or else they'd re-run the LASSO with conditions about not including nonlinear terms without including the lower dimensional terms. Or else they'd run a grouped LASSO and make up some justification for the groups. All of these reveal that most ML practitioners are basically just doing alchemy.

And this is talking about what amounts to a minor version increment of linear regression, so probably the simplest possible technique we'd still call part of ML.
Examples of such plays. And why getting Trump in this ?
And what do you do when you go through all of that time and effort (and potential expense) and get the very likely outcome that the claimant is not in your home jurisdiction?
"forced to wake up to go to school" implies you were a night owl back then too.