HDTenEightyP/NetNews huggingface dataset:
From: j4loucks@student.business.uwo.ca (John Loucks)
Subject: Re: NeuralWorks wanted
Organization: University of Western Ontario
Date: Mon, 28 Sep 1992 18:05:10 GMT




You can try the FAQ section, they quote the authors of that program, NeuralWare Inc. in Pennsylvania.

> Is there anyone can give me the address where I can give a purchase order
> of NeuralWorks Professional 2+?  We would like to use this commercial softwar
> to do some researches.            
> 
> In addition, my friend would like to know the address where he can order
> a software "Brainmaker Professional" ?   
> 
> Thank You!!!
> 
> Steven Huang


j4loucks@student.business.uwo.ca (John Loucks)
Western Business School  --  London, Ontario
From: feuille@sc2a.unige.ch
Newsgroups: comp.ai.neural-nets
Subject: To much Parameter in BackProp
Date: 3 Oct 92 09:49:24 GMT
Organization: University of Geneva, Switzerland


    I am actually using the BackProp algotithm on a relatively small
training set. Especially the number of connections in the 
architecture I am using (3 layers: Input, Hidden, Outpout) comes
close to the number of examples in the training set.
    Is it fair to say I have to much parameters in my system
and that I could even learn random data ?  In fact I evaluate the
performances of the trained network on the test set and they are 
acceptable.
   The underlying  question is in fact: Are the neurons in the
hidden layer the only 'real' parameters of the system since they mix
and transform the inputs ???

  I'll be intested if you have hints on the matter or of you
know references that deal with it.

    Thanks in advance ....

Feuilleauboi Eric
Institut de Topologie et de Dynamique des Systimes (IToDyS)
Universitie Paris 7
1 rue guy-de-la-brosse
75005 PARIS
FRANCE
E-mail 'feuilleauboi@jupiter.itodys.jussieu.fr" or 134.157.24.2
Newsgroups: comp.ai.neural-nets
From: alfred@dec25.lnt.e-technik.tu-muenchen.de (Alfred_Nischwitz)
Subject: Paper: Synchronization and label-switching 
Keywords: impulse synchronization, non-oscillating networks, 'integrate-and-fire'model neurons 
Organization:  Lehrstuhl fuer Nachrichtentechnik, Technische Universitaet Muenchen
Date: Mon, 5 Oct 1992 13:16:58 GMT


The following paper has been published in the
proceedings of the International Conference on 
Artificial Neural Networks '92 in Brighton:

       SYNCHRONIZATION AND LABEL-SWITCHING IN NETWORKS OF
             LATERALLY COUPLED MODEL NEURONS

by  Alfred Nischwitz      Lehrstuhl fuer Nachrichtentechnik
    Peter Klausner        Technische Universitaet Muenchen
    Andreas von Oertzen   Arcisstrasse 21, D-8000 Muenchen 2, Germany
and 
    Helmut Gluender       Institut fuer Medizinische Psychologie
                          Ludwig-Maximilians-Universitaet
                          Goethestrasse 31, D-8000 Muenchen 2, Germany

ABSTRACT:

Necessary Conditions for the impulse synchronization in non-
oscillating networks of laterally coupled 'integrate-and-fire'
model neurons are investigated. The behaviour of such networks
for homogeneous stimulations as well as for differently stimulated
subpopulations is studied. In the first case, synchronization 
accurate to fractions of the impulse duration can be achieved by
either lateral inhibition or lateral excitation and in the second
case, good and independent synchronization is obtained within 
subpopulations, if they are separated by unstimulated neurons.

Hardcopies of the paper are available. Please send requests via
email or to the following address in Germany:

  Alfred Nischwitz
  Lehrstuhl fuer Nachrichtentechnik   
  Technische Universitaet Muenchen
  Arcisstrasse 21, D-8000 Muenchen 2, F.R.Germany
  email: alfred@lnt.e-technik.tu-muenchen.de

Alfred Nischwitz
Newsgroups: comp.ai.neural-nets
From: wgliou@iastate.edu (Weih-Guang W Liou)
Subject: Comparison between Neural Network with Bayesian Decision theory
Summary: comparison Neural Network with Baysian Decision theory
Keywords: Neural Network and Back_propogation algorithm
Organization: Iowa State University, Ames IA
Date: Fri, 2 Oct 1992 03:38:14 GMT

Hi, 

  I am trying to work on the comparision between Neural Network
 with Back_propogation Algorithm and Bayesian Decision Theory. 
 I just started several days ago, so if you could give references
 or any information, I will be very appreciated. Thanks in advances.

 Liou at Ames.

 ------------------------------------------------------------------
 Weih_guang (Wolfgang) Liou 
 Tel:(515) 296-7372
 Signal Processing, EE , Iowa State University
 ------------------------------------------------------------------
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
From: bilgic@phoenix.rose.utoronto.ca (Taner Bilgic)
Subject: Re: Fuzzy logic references wanted
Keywords: fuzzy logic references
Organization: University of Toronto, Department of Industrial Engineering
Date: Thu, 1 Oct 1992 19:44:28 GMT

We are also interested in a comp.fuzzy newsgroup here in Toronto as the
grad. students and researchers of MRCO Expert Systems Lab. 

I guess it is time to discuss many issues that people keep on asking
about fuzzy sets, fuzzy systems etc.

--
Taner Bilgic                      bilgic@phoenix.rose.utoronto.ca
Dept. of Industrial Engineering   bilgic@spring.rose.toronto.edu
University of Toronto             Tel:(416) 978-1280
Toronto, Ontario M5S 1A4 Canada   Fax:(416) 978-1279
From: djasson@afterlife.ncsc.mil (Drew Asson)
Newsgroups: comp.ai.neural-nets
Subject: Re: explanability of neural nets...
Date: 5 Oct 92 19:22:46 GMT
Organization: The Great Beyond

In article <1992Oct5.180038.26537@mp.cs.niu.edu> rickert@mp.cs.niu.edu (Neil  
Rickert) writes:
> In article <1992Oct5.155203.14434@m.cs.uiuc.edu> yang@milton.cs.uiuc.edu  
(Der-Shung Yang) writes:
> 
> >                                           It is my intention to 
> >develop a neural net that can "explain" how it reaches a conclusion in
> >a human-comprehensible way.
> 
> Keep in mind that most humans cannot "explain" how they reach a conclusion
> in a human-comprehensible way.

The University of Washington has done some work with explanations of how a
neural net made its decision (if you want to call it that).  It has to do with 
mapping out the decision surface that the neural net models.  If interested, I  
can dig up the reference.

--
djasson@afterlife.ncsc.mil
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
From: nauck@ibr.cs.tu-bs.de (Detlef Nauck)
Subject: Re: Fuzzy logic references wanted
Keywords: fuzzy logic references
Reply-To: nauck@ibr.cs.tu-bs.de (Detlef Nauck)
Organization: TU Braunschweig, Informatik (Bueltenweg), Germany
Date: Thu, 1 Oct 1992 09:28:41 GMT

In article <1992Sep30.150434.10159@tamsun.tamu.edu> emily@azariah.tamu.edu (Emily Glass) writes:
>In article <1992Sep28.191711.996@til.til.com> tanaka@til.til.com (Yokichi Tanaka) writes:
>>In article <25SEP199217120750@utrcv1>, ree@utrc.utc.com (Bob Erickson) writes:
>>|>
>>|> Also: I've seen several postings mentioning the idea of a Fuzzy Logic
>>|> news group. (e.g. comp.fuzzy_logic or comp.ai.fuzzy_logic ...?).
>>|> Is/Was a proposal voted on?  Do you regard fuzzy_logic as part of AI?

stuff deleted

>>I think there now is enough interest in trying to start up
>>a news group.  I think with a news group of its own, the 
>>traffic will pick up, too.  I am not a "net" or "news" guru,
>>but I am willing to do an RFD (request for discussion) when
>>I return from my trip to Japan (November 1).  If someone 
>>wants to before then, go right ahead.  If you want the list of
>>the e-mail addresses, let me know.
>
>Yoke,
>

stuff deleted

>I vote for calling it comp.fuzzy.  Even though fuzzy control is "ai-ish"
>in the broad sense that it is trying to mimic human reasoning, I agree 
>that it should not be under the "ai" hierarchy.
>
>Thanks for taking the initiative on this.
>
>Emily 
>

I also think there should be a fuzzy news group (I said so in
comp.ai.neural-nets a few months ago). 

I regard fuzzy systems as a part of AI, as I do every system using 
methods of approximate reasoning. Fuzzy is used in combination with other
AI techniques, e.g. neural nets, expert systems. So I think the name
of the news group should be comp.ai.fuzzy, but I will also accept comp.fuzzy,
if the majority thinks that people only interested in practical fuzzy control
issues would be driven away by the label "AI".

For those who are interested:

I have assembled a BibTeX-database of 77 references addressing neuro-fuzzy
issues. This file can be obtained by anonymous ftp from
ftp.tu-bs.de (134.169.34.15). Get the (ascii) file fuzzy-nn.bib in the 
directory local/papers.

Detlef.
Newsgroups: comp.ai.neural-nets
From: saswss@hotellng.unx.sas.com (Warren Sarle)
Subject: Re: Noisy backprop- references needed
Originator: saswss@hotellng.unx.sas.com
Date: Mon, 5 Oct 1992 22:37:51 GMT
Distribution: usa
Organization: SAS Institute Inc.
Keywords: backprop, noise, simulation, generalization, references


In article <1992Oct5.192307.1387@cbnewsl.cb.att.com>, apr@cbnewsl.cb.att.com (anthony.p.russo) writes:
|> ...
|> Many people (me included sometimes), add white noise to the input training
|> patterns when using backprop. While I believe this to be a good
|> idea, and remember this very subject being discussed on
|> comp.ai.neural-nets, I would really like a reference or two
|> justifying this procedure.

I'm a statistician and have just begun studying neural networks.
Adding noise to the input is roughly equivalent to what statisticians
call "ridging", as in ridge regression, which is explained in many
texts on multiple regression. I don't have an explicit reference
handy. Closely related topics include shrinkage estimators and
Bayesian regression. The basic idea is to prevent the weights (in the
regression model or neural network model) from taking excessively
large values when the input is ill-conditioned. Adding noise to the
input makes the input better-conditioned and is likely to give you
better estimated weights if large weights are unlikely in the
subjective Bayesian sense.


-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513       those of SAS Institute.
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
From: ree@utrc.utc.com (Bob Erickson)
Subject: Fuzzy logic references wanted
News-Software: VAX/VMS VNEWS 1.41    
Keywords:  fuzzy logic references
Reply-To: ree@utrc.utc.com
Organization: United Technologies Research Center
Date: Fri, 25 Sep 1992 22:12:00 GMT

I am looking for interesting papers relating to fuzzy logic.

I participate in a small group that gets together to study FL.  
We are interested in different:

  uses (controls, databases, clustering, etc.)
  techniques (neuro-fuzzy, fuzzy associative memories, etc.)
  ties and comparisons to other techniques (belief, probability, etc.)

We've been through Kosko's "Neural Networks and Fuzzy Systems" book, 
and about 15 papers so far.  I'd like to know which are your favorites, 
with some really good insights.

Sources for references, especially network archives with papers, etc.
would especially be appreciated.  Also references to papers in journals,
proceedings, etc.  I already have access to prceedings from FUZZ-IEEE '92.

Respond by email.  I'll summarize if there are responses and interest.

Also: I've seen several postings mentioning the idea of a Fuzzy Logic
news group. (e.g. comp.fuzzy_logic or comp.ai.fuzzy_logic ...?).
Is/Was a proposal voted on?  Do you regard fuzzy_logic as part of AI?

Thanks in advance.

------------------------------------------------------------------------------
Bob Erickson                                         #include <disclaimer.std>
ree@utrc.utc.com
United Technologies Research Center
Newsgroups: comp.ai.neural-nets,comp.ai
From: yang@milton.cs.uiuc.edu (Der-Shung Yang)
Subject: explanability of neural nets...
Organization: University of Illinois, Dept. of Comp. Sci., Urbana, IL
Date: Mon, 5 Oct 1992 15:52:03 GMT

Neural nets have long been described as "black-boxes" due to their 
sub-symbolic approaches. Traditional symbolic AI systems, e.g. expert 
systems, usually have the capability to "explain" why a conclusion is
reached. With this explainability, it is much easier to "debug" a system
and to transfer knowledge between systems. It is my intention to 
develop a neural net that can "explain" how it reaches a conclusion in
a human-comprehensible way. I have some ideas, but I need to know what 
is the current research status for this particular topic. Any references
or information (even only remotely related) will be greatly appreciated.
Both follow-ups or emails are welcome.

Thank you very much in advance.


--
DerShung Yang    
yang@cs.uiuc.edu 
Beckman Institute
Univ. of Illinois at Urbana-Champaign
From: palachar@bert.eecs.uic.edu (Prasad Palacharla)
Newsgroups: comp.ai.neural-nets
Subject: NN in C++ book by A Blum
Keywords: NN, C++
Date: 28 Sep 92 18:29:24 GMT
Organization: University of Illinois at Chicago

Hi,

Could any one help running programs in the book "NN in C++" by Adum Blum on BC++
or SUNC++.  I am interested in using classes described in this book but I am
getting errors when I try to run the programs in the diskette.

Thanks for your help.

Prasad.
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
From: tanaka@til.til.com (Yokichi Tanaka)
Subject: Re: Fuzzy logic references wanted
Keywords:  fuzzy logic references
Organization: Togai InfraLogic, Inc.
Date: Mon, 28 Sep 1992 19:17:11 GMT

In article <25SEP199217120750@utrcv1>, ree@utrc.utc.com (Bob Erickson) writes:
|>
|> Also: I've seen several postings mentioning the idea of a Fuzzy Logic
|> news group. (e.g. comp.fuzzy_logic or comp.ai.fuzzy_logic ...?).
|> Is/Was a proposal voted on?  Do you regard fuzzy_logic as part of AI?
|> 

There has been a number of postings asking/requesting a fuzzy
logic news group.  I've been compiling a list of people who
have posted to "comp.ai", "comp.ai.neural-nets", or
"sci.engr.control" regarding fuzzy since July of this year.
I already have a list of about 70 people.

I think there now is enough interest in trying to start up
a news group.  I think with a news group of its own, the 
traffic will pick up, too.  I am not a "net" or "news" guru,
but I am willing to do an RFD (request for discussion) when
I return from my trip to Japan (November 1).  If someone 
wants to before then, go right ahead.  If you want the list of
the e-mail addresses, let me know.

As for the last question, I pretty much have the same opinion
as my cohort, Erik Horstkotte.  It all depends on how widely you
define "AI".  I tend to have a narrow definition of AI, and so
my answer would be "not really".  Sorry for the fuzzy answer. :-)

-- 
Yoke (Yokichi) Tanaka      Togai InfraLogic, Inc.    "fuzzy"
tanaka@til.com             Irvine, California, USA
uunet!til!tanaka           714-975-8522
In case you're wondering ... I am male.
"The more you drive, the less intelligent you are."
Newsgroups: comp.ai.neural-nets
From: R13552@paccvm.corp.mot.com (Taylor Cheng)
Subject: ROBOT PING-PONG CHAMPIONSHIPS
Organization: Motorola
Date: 28 Sep 1992 21:58:09 HKT


The 1992 Robot Ping-pong World Championships was held in Hong Kong in
Sept 28 (Sun). Four teams from Hong Kong, England, Switzerland, and
Sweden competed and results are as follows :-

World Championships: "BATMAN", Institute of Robotics, ETH, Switzerland,
first runner-up    : "CHARLIE V", Highbury College, Portsmouth, England,
second runner-up   : "Citybat 1", City Polytechnic of Hong Kong,
third runner-up    : "GIRL", Lund Institute of Technology, Sweden.

I was one of the audience and was very impressed by their performances.
Conceivably, the four teams should have (or will) published some of their
research findings in technical journals. Could anyone tell me where I can
find those publications? Particularly would like to know what sort of
learning/training techniques are employed.

Best Regards, Taylor
(R13552@paccvm.mot.corp.com)

Newsgroups: comp.ai.neural-nets
From: sassoj@aix.rpi.edu (John J. Sasso Jr.)
Subject: Genetic Algorithms User Group
Organization: Rensselaer Polytechnic Institute, Troy NY
Distribution: usa
Date: Wed, 30 Sep 1992 23:08:18 GMT

    Here's another vote for a genetic algorithms user group!

                             John
From: Larry.Shupe@mailbox.bison.mb.ca (Larry Shupe)
Newsgroups: comp.ai.neural-nets
Subject: Converting Continuous Recurrent BP to Discrete?
Date: 24 Sep 92 23:14:54 CST

Organization: University of Washington

Has anyone written a program to perform time-dependent recurrent
back-propagation in discrete time steps according to the following
equations described by Fernado J. Pineda (1987) and Barak A. 
Pearlmutter (1989)?

Forward equation:

dyi/dt = -(1/a) * yi + (1/a) * f(sum wij * yj)

yi = activity of ith unit.
a = time constant.
wij = weight from unit j to unit i
f = activation function (sigmoid curve in my case)


Backward equations:

dzi/dt = -(1/a) * zi + (1/a) * sum {f'(ur) * wri * zr} + (Targeti - Outputi)

ur = sum wrk * yk
      k

dE/dwij = (1/a) integral(0,T) {zi * f'(ui) * yj} dt


I've tried converting the equations to discrete time steps like this:

   dyi/dt = -(1/a) * yi + (1/a) * f(sum wij * yj)

becomes:

   yi(t+1) - yi(t) = (1/a) yi(t) + (1/a) * f(sum wij * yj(t))
   
   yi(t+1) = (1 - 1/a) yi(t) + (1/a) * f(sum wij * yj(t))

But I can't get the backwards equations to calculate the gradient correctly.
Has anyone else had any success with this sort of thing.  Any help or
pointers to a working program would be appreciated.
--
Larry Shupe
larry@spike.rprc.washington.edu
University of Washington
Primate Center, SJ-50
Seattle, WA 98195

 * Origin: The Electronic Mailbox (1:348/7.0)
From: menoldre@vtcc1.cc.vt.edu (SCOTT STAUFFER)
Newsgroups: comp.ai.neural-nets
Subject: Re: explanability of neural nets...
Date: 5 Oct 92 16:32:00 GMT
Organization: Virginia Tech, Blacksburg, Virginia
News-Software: VAX/VMS VNEWS 1.41

In article <1992Oct5.155203.14434@m.cs.uiuc.edu>, yang@milton.cs.uiuc.edu (Der-Shung Yang) writes...
>Neural nets have long been described as "black-boxes" due to their 
>sub-symbolic approaches. Traditional symbolic AI systems, e.g. expert 
>systems, usually have the capability to "explain" why a conclusion is
>reached. With this explainability, it is much easier to "debug" a system
>and to transfer knowledge between systems. It is my intention to 
>develop a neural net that can "explain" how it reaches a conclusion in
>a human-comprehensible way. I have some ideas, but I need to know what 
>is the current research status for this particular topic. Any references
>or information (even only remotely related) will be greatly appreciated.
>Both follow-ups or emails are welcome.
> 
>Thank you very much in advance.
> 
> 
>--
>DerShung Yang    
>yang@cs.uiuc.edu 
>Beckman Institute
>Univ. of Illinois at Urbana-Champaign

If you graph a set of weights vs. their values this will provide a graphical 
representation of how that neuron is using the input values.  If a high
weight value is seen (a peak) then the neuron is concentrating on that
part of the input vector.  For multilayer networks this is more complex
but it can be estimated by doing vector multiplication.  I have one 
reference sitting on my desk.

Thomsen J.U. and Meyer B.; "Pattern Recognition of the 1H NMR Spectra
of Sugar Alditols Using a Neural Network"; J. Magn. Res., 1989, 84, 212-17

I am in Chemistry so you will have to wade through some other information

Hope this helps.  I am interested in seeing this done.  I think that it
is not an impossible task and I have often wondered if NN are really
black boxes.

Ron E Menold II
MENOLDRE@vtcc1.cc.vt.edu
Department of Chemistry
From: Dan.Perl@mailbox.bison.mb.ca (Dan Perl)
Newsgroups: comp.ai.neural-nets
Subject: Re: Paper on multiresolution neural nets - reference request
Date: 25 Sep 92 02:02:15 GMT

Organization: BNR Ottawa
Reply-To: don't

I may have the paper at home, and maybe even a business card from Richard
Lepage. I will look for it and post a message tomorrow. Keep an eye on the
newsgroup; sorry I cannot send you email, but I have access only to news,
not email. Anyway, it was this year's SPIE Aerospace Sensing Symposium, or
something like that. Damn, I should remember, I presented a paper right
after Richard. Hey, don't you want my paper too? Anyway, wait till tomorrow.

-- 
Dan Perl	(613)763-9411
AccessNode, FiberWorld
Bell-Northern Research, Ottawa

 * Origin: The Electronic Mailbox (1:348/7.0)
From: rkorczyk@sadis05.sa.aflc.af.mil (RICK KORCZYK - SCDR (AI LAB))
Newsgroups: comp.ai.neural-nets
Subject: AI/ES SYMPOSIUM
Summary: Symposium
Date: 25 Sep 92 15:47:09 GMT


         ************************************************************
         *                                                          *
         *                     The Third Annual                     *
         *                                                          *
         *     Artificial Intelligence/Expert Systems Symposium     *
         *                                                          *
         ************************************************************

         What:   Third Annual AI/ES Symposium

         Where:  Kelly AFB, San Antonio  TX

         When:   6-7 October

         Details:  The Public is invited to view exhibitions in AI/ES
                   starting 6 Oct 0900 and ending 7 Oct 1200.
                   On exhibit will be products from AI vendors from all
                   over the United States as well as projects developed
                   for the Air Force.
                   Sponsored by the Communications/Computer Systems
                   Directorate and the Office of Chief Scientist
                   Engineer, the Symposium will also feature workshops
                   featuring Robotics, Neural Networks, and Intelligent
                   Tutorial Systems.
                   Both government and industry leaders will be
                   speaking on the application of this technology.


                   For more information contact:

           Phone:  Kevin Frisbie (512) 925-7611

           E-mail: kfrisbie@sadis02.sa.aflc.af.mil
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
From: erik@maui.til.com (Erik Horstkotte)
Subject: Re: Fuzzy logic references wanted
Keywords:  fuzzy logic references
Organization: Togai InfraLogic, Inc.
Date: Mon, 28 Sep 1992 16:16:10 GMT

In article <25SEP199217235431@utrcv1>, ree@utrc.utc.com (Bob Erickson)
writes:

|> Also: I've seen several postings mentioning the idea of a Fuzzy
|> Logic
|> news group. (e.g. comp.fuzzy_logic or comp.ai.fuzzy_logic ...?).
|> Is/Was a proposal voted on?  Do you regard fuzzy_logic as part of
|> AI?

I was one of the posters (I hope!).  They has been no formal RFD
posted to news.groups, therefore there has been no CFV or vote. I'm
pretty sure that a vote held at this time would fail, simply due to
lack of traffic.  We only seem to get about 2-5 postings a day in
comp.ai relating to fuzzy logic, which probably isn't enough to
justify a separate newsgroup.

As far as whether I regard fuzzy logic as part of AI or not, the
answer is "not really."  The main reason for this is that I'm one
of the dying breed that still thinks that AI is the search for ways
to make computers think *like humans.*  I don't think I've ever
heard anyone seriously claim that humans use fuzzy logic internally,
although fuzzy logic does model certain aspects of human thinking
fairly well.
-- 
Erik Horstkotte, Manager, Software Development, Togai InfraLogic,
Inc.
erik@til.til.com, uunet!til!erik - (714) 975-8522
Standard disclaimer: the preceding are my opinions, not TIL's.
Newsgroups: comp.ai.neural-nets
From: sassoj@aix.rpi.edu (John J. Sasso Jr.)
Subject: FUZZY LOGIC & RBFNs
Organization: Rensselaer Polytechnic Institute, Troy NY
Date: Sun, 27 Sep 1992 21:14:12 GMT

  Can anyone refer me to any articles and/or books (or even your own points
of view) that relate fuzzy logic to radial basis function networks?  Also,
any references to multiresolution, hierarchical learning would be helpful.

                                 John