HDTenEightyP/NetNews huggingface dataset:
From: andersen@elec.uq.oz.au (Hans Andersen)
Subject: Re: Yes I will be interested in a new comp.ai.ga NEWS group.
Organization: Prentice Centre, University of Queensland
Date: Thu, 15 Oct 1992 03:29:25 GMT

rvs1265@ritvax.isc.rit.edu writes:

>I hail this idea and I hope this will happen in the near future.
>I will be willing to help in this respect and will take an active part.

>Thanks,
>good Luck!!
>Sudhakar Somayajula

I also think it's about time to get comp.ai.ga

Hans Andersen
Newsgroups: comp.ai.neural-nets
From: young@elec.uq.oz.au (Steven Young)
Subject: Re: How does one reason about NN's?
Organization: Prentice Centre, University of Queensland
Date: Fri, 9 Oct 1992 05:00:58 GMT

clin@eng.umd.edu (Charles Lin) writes:
>    ... how does one know what
>when a neural network will train or not (say a backpro, or whatever)?
>    ...  Is it possible that
>NN's are too mathematically difficult to properly reason as to whether
>it will converge or not?

There are the results that various loading problems
and other neural network training decision problems
i.e. `Does a set of weights exist such that a given
training problem can be implemented?'
[Stephen Judd's work and Blum and Rivest's results]
There is still a lot of open ground though (I feel)
with the NP-hardness results and the question about
algorithmic convergence is not easy but has it been
proved `hard'?

Steven Young
--
Steven Young       PhD Student  |  Dept of Electrical Engineering
email : young@s1.elec.uq.oz.au  |  University    of    Queensland
                                |  AUSTRALIA 4072 Ph:61+7 3653564
Newsgroups: comp.ai.neural-nets
From: hucka@engin.umich.edu (Michael Hucka)
Subject: Do neurons fatigue?
Reply-To: hucka@engin.umich.edu
Organization: University of Michigan AI Lab
Distribution: comp
Date: Mon, 12 Oct 1992 06:54:55 GMT

Hello,

I would like to try to find out whether there is evidence for fatigue in
neurons.  Specifically, I'm interested in finding out whether there is
evidence for fatigue effects in non-receptor neurons in vertebrates, in
particular in cortical cells.  By fatigue I mean a decrease in responsiveness
of a particular cell as a result of continued stimulation, and not a process
of habituation.

If any of you know about research that deals with this topic, please let me
know via email.
--
-- Mike
_____________________________________________________________________________
Mike Hucka                     | Internet: hucka@engin.umich.edu    
University of Michigan AI Lab  | 1101 Beal Ave., Ann Arbor, MI 48109-2110
Newsgroups: comp.ai.neural-nets
From: hjlee@top.cis.syr.edu (Hyukjoon Lee)
Subject: Request for source codes of ART1 and/or ART2
Organization: Syracuse University, CIS Dept.
Date: Sat, 10 Oct 92 22:56:43 EDT

Hi, netters,

I am looking for source codes of ART1 or ART2, preferably C, Pascal or Lisp.
If anyone has any information, please let me know. I would greatly 
appreciate your help. Thanks in advance.

H.J. Lee

Newsgroups: comp.ai.neural-nets
From: rvs1265@ritvax.isc.rit.edu
Subject: Yes I will be interested in a new comp.ai.ga NEWS group.
Reply-To: rvs1265@ritvax.isc.rit.edu
Organization: Rochester Institute of Technology
Date: Mon, 12 Oct 1992 16:59:32 GMT

I hail this idea and I hope this will happen in the near future.
I will be willing to help in this respect and will take an active part.

Thanks,
good Luck!!
Sudhakar Somayajula
From: wmammel@hoss.unl.edu (Bill Mammel)
Newsgroups: comp.ai.neural-nets
Subject: Groundwater and neural nets
Date: 15 Oct 1992 14:31:22 GMT
Organization: University of Nebraska--Lincoln	
Distribution: world
NNTP-Posting-Host: hoss.unl.edu

Has anybody seen (or done) anything with modelling of groundwater quality
using neural networks?  This is a possible thesis topic and I just wanted
to know what has already been done.


--
Bill Mammel
Department of Chemical Engineering
University of Nebraska-Lincoln
From: qui@mab1.iitb.fhg.de (Quint)
Newsgroups: comp.ai.neural-nets
Subject: Problems with NDS on Sun
Date: 8 Oct 92 16:15:13 GMT
Article-I.D.: iitb.1992Oct8.161513.29881
Organization: Institut fuer Informations- und Datenverarbeitung


Hi neural-netters,

does anyone out there has experience with the 
Nestor Development System on Sun-4 ?

I have it here, and it crashes with a bus error
in the function pw_test_set() (this is, where
dbxtool believes, that it crashes). This function
is not part of ndslib, but belongs to the sunwindow
library. 

The support from Nestor is really bad. It's now 
three months since I have this error, I had a lot
of phones with Nestor Europe and with Nestor US,
but the error is still here.

May be someone out there has the same experience with that IBM-PC
software, which was forced to work on a Sun (it begins
with the security device, continues with the need of
fixed path's and ends with a user interface on Sunview
basis), and can give me a hint, how to get it to work.

You're my last hope !

Thank you very much,

		Franz
--
Franz Quint
Fraunhofer-Gesellschaft, IITB              e-mail: qui@iitb.fhg.de
Fraunhoferstrasse 1                        phone:  +49 721 6091231
7500 Karlsruhe 1, Germany                  fax:    +49 721 6091413
Newsgroups: comp.ai.neural-nets
From: ben@cs.vu.nl (Bruschke BAH)
Subject: Re: explanability of neural nets...
Organization: Fac. Wiskunde & Informatica, VU, Amsterdam
Date: Wed, 7 Oct 1992 10:48:57 GMT

colin@cs.uwa.oz.au (Colin Jones) writes:

>>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.
>
>This sounds very interesting.  Please do post any references if you have them.

I agree, I would like these references too.
			

>Thanx
>Colin.

			Ben Bruschke <ben\@cs.vu.nl>
Newsgroups: comp.ai.neural-nets
From: yang@dante.cs.uiuc.edu (Der-Shung Yang)
Subject: Re: Neocognitron - Fukushima
Keywords: backprop 
Organization: University of Illinois, Dept. of Comp. Sci., Urbana, IL
Date: Wed, 7 Oct 1992 22:01:32 GMT

jssloka@babbage.uwaterloo.ca (Jeffery Scott Sloka) writes:

>Howdy,

>	My name is Scott Sloka and I am a first year master's student studying bio
>medical image processing.  I have come across a paper by Kunihiko Fukushima
>that delineates his Neocognitron architecture for numeral recognition.  I am
>looking for a better reference than his 1983 paper and I am also interested in
>possibly "borrowing" the code that this is written in, if it is available.  I wish
>to modify his algorithm for my own line of research.  If anyone could be of any 
>help it would be greatly appreciated (email, Post...).  Many Thanks in advance.

>		-Scott


This is from FAQ (August):

17. Neocognitron simulator
  An implementation is available for anonymous ftp at
    [128.194.15.32] tamsun.tamu.edu as /pub/neocognitron.Z.tar
  The simulator is written in C and comes with a list of references
  which are necessary to read to understand the specifics of the
  implementation. The unsupervised version is coded without (!)
  C-cell inhibition.

--
DerShung Yang    
yang@cs.uiuc.edu 
Beckman Institute
Univ. of Illinois at Urbana-Champaign
Newsgroups: comp.ai.neural-nets
From: gkirikos@epas.utoronto.ca (George Kirikos)
Subject: SUMMARY: CRSP Stock Database
Organization: University of Toronto - EPAS
Date: Thu, 8 Oct 1992 04:42:37 GMT

Here is the information regarding the Centre For Research in Security
Prices (CRSP - often pronounced "crisp") stock database. This should
provide good data for the training of neural nets, or allow one to do
research in Finance (my area - Ph.D. candidate (Finance), University
of Toronto).


Centre For Research in Security Prices
Graduate School of Business
University of Chicago
1101 East 58th Street
Chicago, IL 60637

Administrative Office: 312-702-7467
      Research Office: 312-702-7275
	          FAX: 312-702-4797

Internet: crsp_mail@gsbacd.uchicago.edu

Description of Database (from the stock file guide)
-----------------------
- covers NYSE, AMEX, NASDAQ
- daily and monthly data
- (you don't have to license the entire set; e.g. we don't have NASDAQ
   at my site)
- data from 1962 for NYSE/AMEX; from 1974 for NASDAQ
- supplied on magnetic tape (I'm not sure, but it may be available on CDROMs)
- 25 million pieces of information (I think the data is in the 1
  Gigabyte range, in terms of file size)
- ** data "should be used only for research purposes by the subscribing
  institution, its faculty and students, or its employees". Anyone not
  in those categories shouldn't have access. Data can't be resold. Royalties
  need to be paid to CRSP for any non-academic or profit-making endeavor,
  and user needs to get prior written consent to do so.
- LOTS of variables, including: complete name histories, CUSIP, share
  classes, tickers, SIC codes; price histories and trading volume; info
  on why a security stopped trading; dividends, stock splits; shares
  outstanding and market capitalization; holding period returns; indexes;
  betas, standard deviations (in supplementary performance data)

- also, a CRSP bond database is also available (corporate and goverment),
  but I haven't used it yet, so you'll have to e-mail CRSP for more info



+---------------------------------------------------------------------------+
| George Kirikos                   Internet: gkirikos@epas.utoronto.ca      |
| Toronto, Canada                 Telephone: (416) 537-1756                 |
+---------------------------------------------------------------------------+
From: bill@nsma.arizona.edu (Bill Skaggs)
Newsgroups: comp.ai.neural-nets
Subject: Re: Do neurons fatigue?
Date: 12 Oct 92 22:11:17 GMT
	<1992Oct12.150107.23013@wixer.cactus.org>
Organization: ARL Division of Neural Systems, Memory and Aging, University of
	Arizona

sparky@wixer.cactus.org (Timothy Sheridan) writes:

   > In article <HUCKA.92Oct12015455@potomac.engin.umich.edu>
   > hucka@engin.umich.edu (Mike Hucka) writes:
   >
   > >I would like to try to find out whether there is evidence for fatigue in
   > >neurons.  Specifically, I'm interested in finding out whether there is
   > >evidence for fatigue effects in non-receptor neurons in vertebrates, in
   > >particular in cortical cells.  By fatigue I mean a decrease in responsiveness
   > >of a particular cell as a result of continued stimulation, and not a process
   > >of habituation.
   >
   > Actually a post would be welcome as well. 

I don't know a *lot* about this topic, but I'll tell you what I do
know.  Central neurons do indeed fatigue, but not under ordinary
circumstances, and not very quickly.  In an epileptic fit, cortical
neurons start blasting away at maximum rate, and it's a process of
fatigue that brings an end to the fit, a few minutes after it begins. 

Many types of neuron show *adaptation*, whereby the rate of firing
rises to a peak soon after the onset of a stimulus and then gradually
decreases to a lower sustained rate.  Adaptation is a "designed"
feature of neurons, dependent on special kinds of ion channels, and is
not a form of fatigue.

	-- Bill
Newsgroups: comp.ai.neural-nets
From: rolls@cis.umassd.edu (Frank Pinto)
Subject: error back-propagation training algorithm
Organization: University of Massachusetts Dartmouth
Date: Thu, 15 Oct 1992 06:26:25 GMT

Hello all

I'm fresh into a gradua

and I have a general question on the computation of the

error value step. How?

Frank
Newsgroups: comp.ai.neural-nets
From: osm8502@summa.tamu.edu (Omezee-SaMe Still)
Subject: Looking for NN packages for Pattern Classification.
Organization: Texas A&M University, College Station
Date: Fri, 9 Oct 1992 17:10:00 GMT

Hi!
I am interested in Neural Net software packages, that can be used
for pattern classification applications. I want to use them for
pattern classification in manufacturing. If anyone knows of some
codes or packages that I can either buy or access (ftp) please let 
me know at this email:
osm8502@summa.tamu.edu

Omez Samoon Mesina.
Texas A & M University,
Dept. of Mech.Engg.  

Newsgroups: comp.ai.neural-nets
From: young@elec.uq.oz.au (Steven Young)
Subject: Re: Mapping BP neural net decision regions.
Organization: Prentice Centre, University of Queensland
Date: Fri, 9 Oct 1992 04:47:42 GMT

overman@ssc-vax.uucp (Tim Overman) writes:
>Is there a kind soul out there that can tell me if there is a closed form
>solution to mapping out the decision region to a three layer feedforward
>neural network. The net has 3 input, 3 hidden, and one output
>neurons and has been trained accordingly. One could obtain scatter
>plots from MontiCarlo simulations but it would be nice to be able to
>predict the decision region boundaries based on some mathmatical
>computation using the trained weights of the network.

If the network consists of threshold networks then the problem
visualization can be done as follows.  The input-to-hidden unit weights
define three planes (in the 3-dim input space).  The hyperplane arrangement
of these three planes splits the input space. into a number of cells.
Each of these cells has a Boolean vector associated with it.  The
hidden-to-output weights define a linear threshold function on the
boolean representations of these cells, and this tells you
the classification of the cells.  Done.

For standard backpropagation networks with sigmoidal (or other continuous-
valued output function) this is harder.  The sigmoidal units in some sense
still define a hyperplane arrangement (If the weights are large then the
sigmoid approaches a threshold function, so you could proceed as above).
The hidden unit representations now are not Boolean vectors but real vectors
in the output range of the sigmoid functions.  One approach would be to
ignore the `linear' of the sigmoid functions initially and check the
classification of the `reduced' cells; that is the cells of the input
space that are in the saturated region of the hidden unit sigmoids.
Does this help?  Or had you thought of all this already?

>Thanks,

>Tim Overman

Steven Young.
--
Steven Young       PhD Student  |  Dept of Electrical Engineering
email : young@s1.elec.uq.oz.au  |  University    of    Queensland
                                |  AUSTRALIA 4072 Ph:61+7 3653564
Newsgroups: comp.ai.neural-nets
From: erik@maui.til.com (Erik Horstkotte)
Subject: Re: Fuzzy System Variable Independence
Organization: Togai InfraLogic, Inc.
Date: Wed, 7 Oct 1992 15:42:00 GMT

In article <1992Oct6.174755.9360@cs.ucla.edu>, cooper@oahu.cs.ucla.edu
(Mark G. Cooper) writes:

|> Do the inputs to a fuzzy logic system (e.g. a fuzzy associative
|> memory)
|> have to be independent or are there any situations where they have
|> to be
|> independent?

There is nothing I've seen that indicates that they have to be
independent.  In fact, I've done several fuzzy systems where the
inputs were partially interdependent.
-- 
Erik Horstkotte, Togai InfraLogic, Inc.
erik@til.til.com, uunet!til!erik - (714) 975-8522
Standard disclaimer: the preceding are my opinions, not TIL's.
From: ycshin@acsu.buffalo.edu (Yong-Chul Shin)
Newsgroups: comp.ai.neural-nets
Subject: Visualization of Aspirin/Migraines file ?
Keywords: Visualization, Aspirin, Migraines
Date: 8 Oct 92 04:00:52 GMT
Followup-To: ycshin@cs.buffalo.edu
Organization: State University of New York at Buffalo / CEDAR Research Group

Hi !

	Is there any one who has a software that can visualize the
neural networks described in Aspirin/Migraines ?  It can be very helpful
in debugging a network design.

Please post or e-mail to me.

Thank you.


Yong-Chul Shin
Newsgroups: comp.ai.neural-nets
From: colin@cs.uwa.oz.au (Colin Jones)
Subject: Re: explanability of neural nets...
Organization: Dept. Computer Science, University of Western Australia.
Date: Wed, 7 Oct 1992 07:58:53 GMT

In <1992Oct5.192246.5257@afterlife.ncsc.mil> djasson@afterlife.ncsc.mil (Drew Asson) writes:

>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.

This sounds very interesting.  Please do post any references if you have them.

Thanx

Colin.
Newsgroups: comp.ai.neural-nets
From: grau@tnt.uni-hannover.de (Oliver Grau)
Subject: Re: Has making a group for Genetic Algorithms b
Reply-To: grau@tnt.uni-hannover.de
Organization: Universitaet Hannover, Theoretische Nachrichtentechnik
Date: Thu, 8 Oct 1992 16:39:31 GMT

In article FwK@news.cso.uiuc.edu, nafpliot@ux2.cso.uiuc.edu (N.N.) writes:
>I don't want to go over old hash, but has the idea of a group for 
>Genetic Algorithms been discussed?  Something like comp.ai.ga?  If not, 
>can this be discussed?  I would like to know if interest in such a group
>is widespread, or if limited to only a few people.
>
>
>Thanks,
>
>Nicholas Nafpliotis
>nick-n@uiuc.edu
>Illinois Genetic Algorithms Laboratory
>University of Illinois, Urbana-Champaign


I'm also interested in such a newsgroup. But Genetic Algorithms are not related
with artificial intelligence. A better name would be comp.al.ga, where "al" stands
for artificial life.



Dipl.-Ing. Oliver Grau
Inst.fuer Theoretische Nachrichtentechnik                         __
University of Hannover                         _   / .    _  _   / _  _ __  
email: grau@tnt.uni-hannover.de               (_) / / |/ (  /   /__/ / (_/ /_/
Newsgroups: comp.ai.neural-nets
Subject: Re: Human intelligence vs. Machine intelligence
From: swann@divsun.unige.ch (SWANN Philip)
Date: 7 Oct 92 09:17:53 +0200
Distribution: world
Organization: University of Geneva, Switzerland

Penrose's book was given a multiple peer review in Behavioral and Brain
Sciences a couple of years back (I haven't looked at it but no doubt it
covers the psychology side pretty well). I understood Penrose's argument
as going: computation is a model of/from classical mechanics, classical mechanics
is not the whole truth about physical systems (let alone biological ones)
and cannot therefore be and adequate model of the mind.  

Whoever assigned the original poster the topic for a paper must have
a cruel sense of humour! You might as well ask someone to write a paper
on "Capitalism vs Communism".

Philip Swann
University of Geneva 
Newsgroups: comp.ai.neural-nets
From: jssloka@babbage.uwaterloo.ca (Jeffery Scott Sloka)
Subject: Neocognitron - Fukushima
Keywords: backprop 
Organization: University of Waterloo
Date: Wed, 7 Oct 1992 21:11:18 GMT

Howdy,

	My name is Scott Sloka and I am a first year master's student studying bio
medical image processing.  I have come across a paper by Kunihiko Fukushima
that delineates his Neocognitron architecture for numeral recognition.  I am
looking for a better reference than his 1983 paper and I am also interested in
possibly "borrowing" the code that this is written in, if it is available.  I wish
to modify his algorithm for my own line of research.  If anyone could be of any 
help it would be greatly appreciated (email, Post...).  Many Thanks in advance.

		-Scott
From: batra@boulder.Colorado.EDU (sajeev batra)
Subject: some questions on PAC learning
Organization: University of Colorado, Boulder
Date: 11 Oct 92 06:28:52 GMT

__________


first, i would like to apologize if these questions have been asked 
before.

i am trying to learn about this  PAC (probably approximately correct)
learning concept.  What does it mean for something to be pac-learnable?

the term Vapnik-Chervonenkis (VC) dimension is thrown about 
quite often.  Where does this fit in?

and one more thing...  I have been trying to read Valiant's "Theory
of the Learnable" (Comm. of ACM, 1984, 1134-1142) paper.  I do not
understand it.  Could someone who has read it briefly summarize it at 
a level that i could comprehend (introductory level).  I have a small
background in neural nets and statistics.

posting or emailing comments would be good.  And please
try to make all points in an introductory level.

thank you.
sajeev.

____________
Newsgroups: comp.ai.neural-nets
From: scotbri@flower.samsung.com (Scott Brigham, corp)
Subject: Re: Noisy backprop- references needed
Originator: scotbri@flower
Organization: Rosemount, Inc.
Distribution: usa
Date: Thu, 8 Oct 1992 14:09:11 GMT

From article <Bvpp9F.617@epix.rrze.uni-erlangen.de>, by arras@bfws46.forwiss.uni-erlangen.de (Mike Arras):
> 
> In article <Bvoo1v.IIq@uxa.ecn.bgu.edu>, mgcbo@uxa.ecn.bgu.edu (Charles B. Owen) writes:
>> ...
>>Adding noise (and white noise is a bad choice, normal or
>>gaussian is better), to the wieghts (and sometimes just the inputs,

Talking about white noise vs. normal or gaussian is an apples and oranges
thing.  "White" refers to the spectral content whereas "normal or 
gaussian" refers to the statistical distribution.  You can have gaussian
noise that is white or "colored".

Perhaps you meant to make the distinction between gaussian and uniform
statistical distributions.
=======================
scotbri@rosemount.com
Scott Brigham
Rosemount, Inc.
Eden Prairie, MN
=======================
From: asif@sunlite.concordia.ca
Newsgroups: comp.ai.neural-nets
Subject: Re: Noisy backprop- references needed
Keywords: 2 DOF, Simulated Annealing
Date: 8 Oct 92 06:19:29 GMT
Reply-To: asif@sunlite.concordia.ca ()
Organization: Concordia University, Montreal Quebec
Originator: asif@tiros



Hello:

Maybe this will help. 
We were training a network to simulate the forward and inverse dynamics of 
 a 2 DOF robot manipulator. While this does not sound like a complex task, we had
a lot of difficulty in acheiving convergence. That is until we did simulated annealing on the process. Immediately within a matter of 50-100 epochs the network quickly converged to a stable minima. Again as it was descending we furthered the process of annealing and the error went down but not considerably. We feel we arrived at the global minima. We have not been able to get a plot of the error surface of this network. 

We are using a package called PlaNet on a Sun Sparc workstation. The simulation time for a 1 hidden layer ( 2-40-2 ) learning forward dynamics was approximately 6.5 hours whereas for inverse dynamics (2-40-2) was approximately 8 hours. 
We tried for 10000 epochs in both cases.

We also tried traing a 2 hidden layer network. However, for some strange reason it is not converging at all. Completely baffles us. structure 2-40-20-2
Any suggestions

Thanks

Asif
From: fernando@eemips.tamu.edu (Susith Rohana Fernando)
Newsgroups: comp.ai.neural-nets
Subject: E-mail address of Michael A. Franzini
Date: 9 Oct 92 16:57:33 GMT
Article-I.D.: tamsun.1992Oct9.165733.836
Organization: Texas A&M University

Hi,

I wonder anybody knows how to contact Michael A. Franzini? I believe he was
with the Dept. of Computer Science at CMU around 1989. I don't know whether
he is still there or not. I prefer an e-mail address, but even a phone 
number would be really helpful. Thank you in advance.

Susith Fernando(fernando@eemips.tamu.edu)

Dept. of Electrical Engineering
Texas A&M University
College Station, Tx77840
Newsgroups: comp.ai.neural-nets
From: eskfoo@ntuvax.ntu.ac.sg
Subject: REFERENCE NEEDED: Parallel BackProp Implementation
Organization: Nanyang Technological University - Singapore
Date: Wed, 14 Oct 1992 07:29:55 GMT

Hello EveryBody
	
	I'm a postgraduate student doing research in NN. Presently I'm
intending to implement the backpropagation algorithm using 3L Parallel C
language. I am using 4 Inmos transputer (model T800). I'm looking for any
references related to the above parallel implementations.

	Any form of references or source code is fine with me.

	Thanks and
	Good Bye