HDTenEightyP/NetNews huggingface dataset:
From: apr@cbnewsl.cb.att.com (anthony.p.russo)
Subject: Noisy backprop- references needed
Organization: AT&T Bell Laboratories
Distribution: usa
Date: Mon, 5 Oct 1992 19:23:07 GMT
Keywords: backprop, noise, simulation, generalization, references

I am reviewing a book chapter on backpropagation and would
appreciate help with the following:

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.

The author and I would appreciate any help you can give.

Thanks in advance,

Anthony Russo


	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
	~  	 Tony Russo		" Surrender to the void."	~
	~  AT&T Bell Laboratories					~
	~   apr@cbnewsl.att.com OR apr1@homxc.att.com			~
	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

-- 

	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
	~  	 Tony Russo		" Surrender to the void."	~
	~  AT&T Bell Laboratories					~
From: David.Martland@brunel.ac.uk (David Martland)
Newsgroups: comp.ai.neural-nets
Subject: INNS Ballots
Date: 30 Sep 92 11:46:18 GMT
Organization: Brunel University, Uxbridge, UK
X-Newsreader: Tin 1.1 PL3

I've just opened my mail, and found a ballot form for INNS elections.

Who's running the INNS at present? When I came to put the form into the
envelope supplied I noticed that I am expected to provide my signature and membership
number on the outside, and doubtless following US practice I should include my
address as well. 

Should I also supply my telephone number and a list of all my bank accounts and credit
card numbers? Perhaps I'm paranoid, but my wife once had a cheque book stolen, and since she
had to sign official notices which were posted for all and sundry to read, the thief had a
relatively easy time for a while. There is a trick - don't use your "normal" signature for
such visible signings e.g. use initials rather than first names, or vice-versa, and this will
eventually help in negotiations with banks if you do have this problem!

I shall post my ballot in a new envelope, and sign the form.

Dave Martland
Newsgroups: comp.ai.neural-nets
From: falex@loria.fr (Frederic Alexandre)
Newsgroups: comp.ai.neural-nets
Subject: Re: References wanted
Date: 30 Sep 92 11:07:43 GMT
Distribution: comp
Organization: CRIN (CNRS) Nancy - INRIA Lorraine

In article <PERERICO.92Sep19124437@pinus.slu.se>, pererico@pinus.slu.se (Per-Eric Olsson) writes:
|> Hello,
|> 
|> I have recently read the book "AN ADAPTIVE NEURAL NETWORK, the cerebral
|> cortex", by Y.Burnod. (first published 1988). The ideas seems quite
|> interesting, though there are some obvious errors in the (as it seems) hastily
|> typeset book.
|> 
|> Because of the complexity of the topic I am sure there should be some further
|> deep/detailed studies. Therefore I would be interested in any comments and
|> references to further research based on this idea. I would also appreciate any
|> references to other brain models.

A group of computer scientists in Nancy has been working with Y. Burnod's team
in Paris since 1987. We adapted his model to computer science and proposed
some applications including speech processing, image interpretation and control.
The main references published in english are:

F. Guyot, F. Alexandre, J.P. Haton, "Toward a Continuous model of the
cortical column: application to speech recognition", Proc. ICASSP-89, Glasgow,
1989.

Alexandre, F., Guyot, F., Haton, J.P. (1990) "A connectionist
network with two complementary visual processing systems for x-ray
image interpretation", INNC'90, Paris.

Guyot, F., Alexandre, F., Haton, J.P. (1990) "Principles and
 applications of the cortical column symbolic neural model", IJCNN'90,
 San Diego.

Alexandre, F., Burnod, Y., Guyot, F., Haton, J.P. (1991) "The
  Cortical Column: a new processing unit for multilayered networks",
  Neural Networks, Vol 4, n 1, pp. 15-25, 1991.

As you remark, the topic is complex. Our implementations are a simplification
of Burnod's model. Nevertheless, we still work with him and improve the model.
I hope this will help. If you want some more details on these papers or on 
the ongoing work, contact me.

 alex

Frederic ALEXANDRE
CRIN-INRIA
BP 239
54506 Vandoeuvre-les-Nancy
FRANCE
E-mail: falex@loria.fr
Phone: (33) 83 91 24 26
Newsgroups: comp.ai.neural-nets
From: hoekstra@cs.utwente.nl (Aarnoud Hoekstra)
Subject: e-mail address wanted
Organization: University of Twente, Dept. of Computer Science
Date: Fri, 2 Oct 1992 07:44:25 GMT

Dear Netters,

I am looking for the e-mail address of mr. V.V. Tolat. As far as I know he's working
at Stanford University (CA), Department of Electrical Engineering. If anyone knows
his address, please let me know.

Thanks in advance.


Aarnoud Hoekstra
Dept. of Computer Science
University of Twente
The Netherlands

hoekstra@cs.utwente.nl
Xref: sparky comp.ai.neural-nets:3790 comp.theory:2146
From: MICHAEL.WILLETT@OFFICE.WANG.COM ("Michael Willett")
Subject: Re: Traduction Automatique
Organization: Mail to News Gateway at Wang Labs
Date: 05 Oct 92 11:11:17 EST

Regarding the request for information on automated translation
(traduction automatique), I would suggest that interested people
contact probably the leading industry "guru" on this technology,
Miguel Brazao.  A former Wang Laboratories director of international
products, he has also been associated with Bull translation
strategy.  He has developed some exciting new concepts, especially
regarding the use of artificial intelligence and natural language
normalization, making substantial improvements in the efficiency and
effective language translation work.  He can be contacted at the
Burlington, Mass. (US) firm Peritus.  It is best to send him a FAX
since he is normally out at customer sites.  His FAX there at
Peritus is (617) 221-7122.  Since he is perfectly fluent in French,
Spanish, Portuguese, and Italian, you can send him a FAX in any of
these languages.

Michael.Willett@OFFICE.Wang.com
Newsgroups: comp.ai.neural-nets
From: geb@engr.ucf.edu (Georgios Bebis)
Subject: "Benchmarking and fast learning in neural networks .... "
Organization: engineering, University of Central Florida, Orlando
Date: Sun, 27 Sep 1992 22:27:43 GMT

I am looking for a paper by A. Veitch & G. Holmes, entitled
"Benchmarking and fast learning in neural networks: Results
for Back-propagation", Proceedings of the Second Australian
Conference on Neural Networks, pp 167-171, 1991.
I'm wondering if its electronically available anywhere.
If not, any help for obtaining a copy of it, is greatly appreciated.

Thanks,

George Bebis
Dept. of Electrical and Computer Engineering
University of Central Florida, Orlando
Newsgroups: comp.ai.neural-nets
From: datwyler@javelin.sim.es.com (Doug Datwyler)
Subject: morse code decoding
Summary: I would like some help with journal names covering the subject. a
Keywords: morse neural fuzzy
Reply-To: datwyler@javelin.sim.es.com
Organization: Evans & Sutherland Computer Corp., Salt Lake City, Utah
Date: Mon, 5 Oct 1992 15:42:22 GMT

I would like some assistance finding article names and references dealing
with the decoding of morse code. Either neural, fuzzy, or both could be used.
I have been assured that it is easy, but I am a beginner at this stuff. I have
access to a university library.

Thanks.

-- 
Douglas L. Datwyler, WR7O
Evans & Sutherland Computer Corp.
datwyler@javelin.sim.es.com
From: tmw@festival.ed.ac.uk (Tom WRight)
Newsgroups: comp.ai.neural-nets
Subject: Rochestor simulator file needed
Date: 30 Sep 92 16:25:40 GMT


I know this shouldn't be on the net but I
could'nt find an email address.

I've unpacked the code for the simulator
and tried to build it, but I'm missing 
the file ranlib.h 

Could anybody email this to me thanks

(Or am I doing something wrong and I don't
really need this)

Thanks
From: fzgabor@chip.ucdavis.edu (Andy Gabor)
Newsgroups: comp.ai.neural-nets
Subject: Re: Summary: wavelet digest
Date: 28 Sep 92 17:02:43 GMT
Organization: Dept. of Neurology, University of California, Davis


In article <17576@ucdavis.ucdavis.edu> fzgabor@chip.ucdavis.edu (Andy
Gabor) writes: 

>I understand that there is a "wavelet digest" to which one may subscribe. 
>I think it is at scarolina.edu but my attempts to email a request to
>subscribe have failed.  If someone knows the correct email address I would
>appreciate being advised by email or the net.
>

Many thanks for all the responses to my query.  Several requests to
forward information also recieved, therefore this summary.

To subscribe: email:   'wavelet@math.scarolina.edu'.        
              subject: 'subscribe'.

To submit article: email: same address.
                   subject: 'submit'.

Anonymous FTP archive site: 'maxwell.math.scarolina.edu' or 
                            '129.252.12.3'
                 directory: '/pub/wavelet/archive'

Many thanks again for all thoughtful responses (no attributions in
order to save space.

I have emailed to subscribe and so far mail was not returned as 'unknown
host'.  An attempt to access archives was successful. 

Interesting note: 'finger @math.scarolina.edu' returns 'unknown host'. 

Many thanks again for all thoughtful responses (no attributions in order
to save space). 

Andy

*******************************|
Andy Gabor                     |
Department of Neurology        |
University of California, Davis|
(email) ajgabor@ucdavis.edu    | 
*******************************|
From: sunjain@matt.ksu.ksu.edu (mera bharat mahan)
Newsgroups: comp.ai.neural-nets
Subject: wanted C code for backpropagation and BAM
Date: 3 Oct 1992 15:41:30 -0500
Organization: Kansas State University
NNTP-Posting-Host: matt.ksu.ksu.edu

hi.

   I am just a beginner in Neural Networks. To start with I need some
code written in C for backpropagation and BAM. (for UNIX)

Further has anybody tried asyncronous learning techniques for Backpropagtion
and BAM?

thanks in advance.

sunil jain. 
Newsgroups: comp.ai.neural-nets
From: more@tk2.oulu.fi (Jyrki Alakuijala)
Subject: Questions on classification requirements?
Reply-To: more@stekt.oulu.fi
Organization: University of Oulu, Dept. of EE, Finland
Distribution: comp.ai.neural-nets
Date: Thu, 1 Oct 1992 10:11:30 GMT

I have developed a method for vector classification. It seems to be
faster than anything I have used before. This method can learn about
1000 vectors in a two spirals problem (each 14 revolutions) in one
second on my sun 3/50. The 100% correct mapping is learned in about a
minute. The complexity of calculation as a function of vector
dimension is N and as a function of class border complexity log N. So,
the algorithm does not slow down even with some 10000 classes (or
codebook vectors). When not learning, the algorithm is still a little
bit faster. In any real-world case the algorithm will be just one
order-of-magnitude slower than any optimal parallized algorithm. This
suggest that the use of neural methods for vector classification is
not needed :-)

There are also some other good things in it: multiple levels of
abstraction are created in the learning and it can self-organize (ie.
to learn reasonable classification of set of vectors just like kohonen
feature map).

The tradeoff with the speed and everything has been convex and rough
class borders (not even voronei-tesselation) and about three times the
memory consumption of conventional algorithms. However, with the
increased speed and ability to handle any amount of "code-book"
vectors this should not such a big problem, if you have enough data to
teach the the nice class borders to the algorithm.

I would like to have answers to following questions to fine tune the
algorithm. (It can be tuned for voronei-tesselation with some slow
down and/or worse multi-level abstraction.) 

So, what do you value in the vector classification:
- Multiple levels of generalization (2 to 20) with the deepest level
  of "perfect match" to the teaching set versus single level of
  generalization 
- Non-surprising class borders (for example voronei-tesselation)
  versus "ok for the teaching set, but.." (in other words: is it
  required to learn good class borders from single sample of the class?)
- Speed (self-organizing / learning / using)
- Memory consumption
- Continuous non-linear class borders versus piecevice linear class borders
- Something else?

Please reply by e-mail, I will summarize.
--
Jyrki Alakuijala - Atraintie 6, 90550 Oulu, Finland, +358-81542334
From: robillac@ERE.UMontreal.CA (Robillard Christian)
Newsgroups: comp.ai.neural-nets
Subject: Need ART2 algorithm
Date: 29 Sep 92 20:50:30 GMT
Organization: Universite de Montreal


  I was wondering if there was a charitable person out there in bit land
that could send me S.Grossberg's ART2 algorithm in either FORTRAN,
PASCAL or C for a SUN4 system. I would appreciate greatly if you could
enlighten me on this algorithm as I am from operations research. I need
this algorithm for clustering continuous coordinates.

  Thanks in advance.
-- 
Christian Robillard                E-mail: robillac@brise.ERE.UMontreal.ca
Universite de Montreal
Xref: sparky comp.ai.neural-nets:3682 comp.ai:3678 sci.engr.control:100
From: luit1@wsinfo11.info.win.tue.nl (Wim Jansen)
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
Subject: Re: Fuzzy logic references wanted
Keywords: fuzzy logic references
Date: 30 Sep 92 09:23:17 GMT
Reply-To: luit1@info.win.tue.nl
Followup-To: comp.ai.neural-nets

erik@maui.til.com (Erik Horstkotte) writes:

>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.

I agree. At this moment there is not enough support for a 'fuzzy' group.

>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.

I have to disagree with you here. Although humans do not use fuzzy logic in
the process of *thinking*, they do use it in the process of *thinking
about*. My point is that you are absolutely correct, if you say that neural
networks have not much in common with fuzzy logic. However, fuzzy logic is
a very good model for reasoning of humans.
 I always though that the main difference between a machine and a human was
the accuracy with which they work. Computers calculate with discrete
quantities, whereas humans use inaccurate (fuzzy) measurements.

Wim Jansen


>-- 
>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.
-- 
======================================================================
=         -- Another Key-bored Genius gets Mouse-trapped --          =
=        luit1@info.win.tue.nl ( in real life: W.M. Jansen )         =
======================================================================
Newsgroups: comp.ai.neural-nets
From: morlan@afit.af.mil (Bruce W. Morlan)
Subject: Re: Scientic American Sept 92, code anybody?
Organization: Air Force Institute of Technology
Date: Wed, 30 Sep 1992 13:23:56 GMT

tmw@festival.ed.ac.uk (Tom WRight) writes:

>Does any body have the code for the amateur scientist 
>article in the Sept issue of Sci Am.

Yes, I coded up a version that is recognizable as such - very short.
By only allowing two features I was able to graph the locations of
the first layer separating hyperplanes (conics, in this case) as the
net learned the sample data.  I'll try to post the executable and
supporting files (zipped and UUENCODEd) as soon as I figure out how to 
UUENCODE (e-mail hints accepted gladly).

I will be presenting the results of this (as applied to the identify-
friend-or-foe problem) at the November meeting of ORSA/TIMS (in San
Fransisco).
-- 
Bruce W. Morlan, Major, USAF             Air Force Institute of Technology
Dept. Department Head                    AFIT/ENC
Department of Mathematics                WPAFB  OH  45433
Newsgroups: comp.ai.neural-nets
From: u913789@tasman.cc.utas.edu.au (Muhammed D Abdullah)
Subject: 3d-object pose estimation
Organization: University of Tasmania, Australia.
Date: Thu, 1 Oct 1992 12:04:00 GMT

i
I am presently doing a BP simulation to determine an object position in space using 3d data. Therefore I would like to know whetheranybody else on the net is doing a research upon the subject as well, I need to discuss a few things concerning the problems faced when using 3d data (if any) for ANN training.
:wq
From: banfield@asterix.cs.mcgill.ca (Stephane BANFIELD)
Newsgroups: comp.ai.neural-nets
Subject: References wanted on Speech Recognition using Nerual Nets
Keywords: Neural Networks, Speech Recognition.
Date: 2 Oct 92 18:01:23 GMT
Organization: SOCS, McGill University, Montreal, Canada

Hi Netters,

I have to start writing a report on Speech Recognition using Neural Networks.
Could someone give me some (main) references on that subject please. 

Also, could someone tell me what is THE reference book for Neural Networks (I  
mean the 'Bible' for Neural nets).

Thankyou,
		steph.


--

Stephane Banfield 	
----------------------------------------------------------------------
- McGill University - School of Computer Science - Montreal, CANADA  /
- Universite de Quebec a Montreal (UQAM) - Montreal, CANADA          \
- Universite de Technologie de Compiegne (UTC) - Compiegne, FRANCE.  /
 __________________________________                                  \
|   ___                            |    |  " Sometimes a cigar       /
| /|   |                           |    |    ... is just a cigar "   \
| \|___|  e-mail :                 |    |                            /
|                                  |    |   Sigmund Freud......      \
|         banfield@cs.mcgill.ca    |    |                            /
|         banfield@info.uqam.ca    |    |----------------------------\
|                  ______________  |    |                            /
|  tel:           | TELECARTE 50 | |    |    JUGGLING FOREVER....... \
| (514) 284-3697   --------------  |    |                            /
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Newsgroups: comp.ai.neural-nets
From: bryant@neural.Kodak.COM (Steve Bryant)
Subject: Stock Market Database
Organization: Eastman Kodak Co., Rochester, NY
Date: Tue, 6 Oct 92 15:14:27 GMT

Does a stock market performance data base exist for any of the 
popular indexes? I would like to test a network against stock
market prediction.
Newsgroups: comp.ai.neural-nets
From: hueske@iw.uni-hannover.de (Marc Hueske)
Subject: neuro-fuzzy-controller
Reply-To: hueske@iw.uni-hannover.de
Organization: Institut fuer Werkstoffkunde, Uni Hannover
Date: Tue, 6 Oct 1992 15:21:28 GMT

Our project is to develop a Neuro-Fuzzy-Controller for an underwater vehicle
(ROV, AUV). We would like to know if there is any literature about this or similar
subjects. Furthermore we are interested in PD-software about neuro-fuzzy.

Thanks in advance,

Marc Hueske
From: tmw@festival.ed.ac.uk (Tom WRight)
Newsgroups: comp.ai.neural-nets
Subject: Scientic American Sept 92, code anybody?
Date: 30 Sep 92 11:31:51 GMT

Does any body have the code for the amateur scientist 
article in the Sept issue of Sci Am.


Thanks
From: jamesk@uxmail.ust.hk (Kwok Tin Yau)
Subject: Bayesian classifier fails to separate ??
Organization: Hong Kong University of Science and Technology
Date: Wed, 30 Sep 1992 01:23:13 GMT

-- 
James Kwok                       |   The Hong Kong University of     |
Internet: jamesk@uxmail.ust.hk   |     Science and Technology        |
                                 |  Department of Computer Science   |
Xref: sparky comp.ai.neural-nets:3745 comp.ai.philosophy:6285 sci.cognitive:474
From: erwin@trwacs.fp.trw.com (Harry Erwin)
Newsgroups: comp.ai.neural-nets,comp.ai.philosophy,sci.cognitive
Subject: Report Received
Keywords: chaos neuroscience
Date: 4 Oct 92 01:04:45 GMT
Followup-To: comp.ai.philosophy
Organization: TRW Systems Division, Fairfax VA


Freeman, Walter J., 1992. "Neural Networks and Chaos," INNS Above Threshold,
Fall 1992.
 
This paper provides a review of brain functions that underlie perception and
motor control, in the context of the contribution of chaotic dynamics to the
functions of memory and recall.
 
Background: I believe we're between 2 and 10 years away from building a
cognitive machine.  Freeman's work provides insight into how that machine
might be built. Based on his results and other work, I propose that the
cognitive machine will not be a von Neumann machine, but will use chaotic
processing instead. Other design features will be the downloading of tracking
programs to the sensor processors to track specific objects in real time,
the use of non-linear models of the behavior of specific objects defined
semantically, redirection of sensory data streams, reprocessing of sensory
data streams, efficient parallel algorithms for pattern recognition, dualistic
heuristic programming for the control of motor actions, pseudo-holographic
memory storage, and attention handled by recognition and suppression
processes. We may also use complex neuron models involving dynamic
switching in dendritic arbor and non-linear FM readouts at the axon.

Read the paper and see the movie 8)
-- 
Harry Erwin
Internet: erwin@trwacs.fp.trw.com
From: yewhan@tartarus.uwa.edu.au (Yew Han Hee)
Newsgroups: comp.ai.neural-nets
Subject: Q: FSA & Neural-net, relationship?
Date: 7 Oct 1992 03:00:15 GMT
Organization: University of Western Australia
NNTP-Posting-Host: tartarus.uwa.edu.au
X-Newsreader: Tin 1.1 PL5

Hello,

I am currently doing a project related with Finite State Automaton, and
I should find a relationship between FSA and Neural-net, could someone
please give me some idea how they are related with each other? Just a
brief idea will do! Please send e-mail to me, or if you like, please
continue to post it to this tread, it will be great to share the idea
with somebody else who like to know!

Thanks in advance!

Sincerely,
yewhan.
-----------------------------------------------------------------------
                             Yew Han Hee 
     yewhan@tartarus.uwa.edu.au    hee_y@dropbear.cs.uwa.edu.au
     University Of Western Australia, Computer Science 2nd year          
-----------------------------------------------------------------------
                   Avoid all evils, Do all goods; 
        Cleanse your Heart, That's all the teaching of Buddha. 
-----------------------------------------------------------------------

Newsgroups: comp.ai.neural-nets
From: danz+@CENTRO.SOAR.CS.CMU.EDU (Dan Zhu)
Subject: # of training samples <-> # of input, # of output
Originator: danz@CENTRO.SOAR.CS.CMU.EDU
Organization: School of Computer Science, Carnegie Mellon
Date: Wed, 30 Sep 1992 04:52:53 GMT


   
    Has anyone come across any papers analyzing the rules of thumb about the
relations among the number of training samples, number of inputs and outputs or
number of hidden nodes? For example, how many number of training examples
are required for a given number of input and out parameters? I remember I've 
seen one, but I couldn't recall where. 

    Any pointers or comments will be greatly appreciated.

    Thanks in advance!