HDTenEightyP/NetNews huggingface dataset:
From: Frank.Diiorio@launchpad.unc.edu (Frank Christopher DiIorio)
Subject: DOS software wanted
Organization: University of North Carolina Extended Bulletin Board Service
Date: Thu, 7 Jan 1993 20:50:15 GMT

I'm looking for neural net software which will run on a PC running any of
DOS, Windows, or OS/2. The application is (in very general terms) trying
to simulate/understand patterns of business strategy shifts over time.
Any opinions? Thanks in advance for your help.

Frank DiIorio

(also reachable at internet address shank@uncvx1.oit.unc.edu)
--
   The opinions expressed are not necessarily those of the University of
     North Carolina at Chapel Hill, the Campus Office for Information
        Technology, or the Experimental Bulletin Board Service.
           internet:  laUNChpad.unc.edu or 152.2.22.80
From: U27839@uicvm.uic.edu (venky Gopalaswamy)
Newsgroups: comp.ai.neural-nets
Subject: need some pointers!!
Date: 6 Jan 93 00:23:53 GMT
Organization: University of Illinois at Chicago

I need some informationon the application of ANN for reliability/availability
prediction.  Also needed are the prediction methods/algorithms used and their s
ensitivity.  Being a beginner in this field I need as much help I could get.  T
hanks in advance
From: tgorb@rrc.chevron.com (Joe Gorberg)
Newsgroups: comp.ai.neural-nets
Subject: Re: Neural-nets and horse racing?
Date: 8 Jan 93 15:15:06 GMT
Reply-To: tgorb@rrc.chevron.com
Organization: Chevron, Richmond, California

In article 1iiageINN1p3@MINERVA.CIS.YALE.EDU, theodore-michael@yale.edu (Dr. Disorder) writes:
>Yes, I know I'm a moron for even asking this, but that aside, could anyone
>point me in the direction of prior research regarding neural-nets and
>betting on horses (or just betting generally)? It seems like enough data
>is available to train a network to intelligently pick enough winners so that
>one would come out ahead (over the long haul).
>
 
Talk to the folks at Ward Systems Group Inc., the maker of Neuroshell and 
Neurowindows.  One of the examples that comes with Neuroshell is a net
for playing the horses.

Ward Systems Group phone #: (301) 662-7950.


Joe Gorberg
tgorb@rrc.chevron.com
From: timh@meaddata.com (Tim Humphrey)
Newsgroups: comp.ai.neural-nets
Subject: email address for Watkin's thesis
Date: 5 Jan 1993 22:35:00 GMT
Organization: Mead Data Central, Dayton OH
NNTP-Posting-Host: neuron.meaddata.com


I'm looking for an email address for someone at Cambridge U.,Cambridge, 
England, so I can send a request for C.J.C.H. Watkin's 1989 disertation,
"Learning from Delayed Rewards".

Tim Humphrey
timh@meaddata.com
Newsgroups: comp.ai.neural-nets
From: evol@infko.uni-koblenz.de
Subject: Technical report on topology optimization of anns available
Organization: University of Koblenz, Germany
Date: Thu, 07 Jan 1993 06:12:04 GMT

Our new Technical Report "Synthesis and Performance Analysis of Multilayer
Neural Network Architectures" is now available via ftp:


	ftp archive.cis.ohio-state.edu  or  ftp 128.146.8.52
	cd pub/neuroprose
	binary
	get schiff.gann.ps.Z
	quit

In this paper we present various approaches for automatic topology-optimization
of backpropagation networks. First of all, we review the basics of genetic
algorithms which are our essential tool for a topology search. Then we give a
survey of backprop and the topological properties of feedforward networks. We
report on pioneer work in the filed of topology--optimization. Our first
approach was based on evolutions strategies which used only mutation to change
the parent's topologies. Now, we found a way to extend this approach by an
crossover operator which is essential to all genetic search methods.
In contrast to competing approaches it allows that two parent networks with
different number of units can mate and produce a (valid) child network, which
inherits genes from both of the parents. We applied our genetic algorithm to a
medical classification problem which is extremly difficult to solve. The
performance with respect to the training set and a test set of pattern samples
was compared to fixed network topologies. Our results confirm that the topology
optimization makes sense, because the generated networks outperform the fixed
topologies and reach classification performances near optimum.



	Randolf Werner
From: paul@davox.UUCP (Paul Kneipp)
Newsgroups: comp.ai.neural-nets
Subject: Backprop Source Wanted
Date: 7 Jan 93 22:38:49 GMT
Distribution: usa
Organization: Davox Corporation, Billerica, MA

I'm looking for a very well documented implementation of a Back propogation neural-net
simulator in "C".

I've read a bit and pulled a couple things off Compuserve, but I really feel that a
well documented piece of source code would serve me best at this point.

If it's relevant, I do X windows programming on a Sun Sparc 2 (unix/C).  I would ultimately like
to produce a graphic NN simulator myself.

I dont receive this news-group here at work, so direct E-mails of source code (or locations
where it may be retreived) are best for me.

I'm a novice at this point, but very enthusiastic!


Thanks

Paul Kneipp
Davox Corp.
Billerica, MA
(508) 667-4455 x267

uunet!davox!paul
From: bs_s511@ceres (Yeghiazarian A)
Newsgroups: comp.ai.neural-nets
Subject: NN in Market Research
Summary: Need to know any references on NN in marketing
Date: 8 Jan 93 14:20:07 GMT
Organization: Kingston University
NNTP-Posting-Host: ceres.kingston.ac.uk
X-Newsreader: Tin 1.1 PL4


Good Day All,

I am thinking in researching in use of NN techniques in Market Research/
Marketing. Is there any one knows references or idea in the above area? 



Cheers,


Ara

Janet: Yeghiazarian@uk.ac.kingston
Internet: Yeghiazarian@king.ac.uk

Tel: (044) 081-547 2000
Fax: (044) 081-547 702
Newsgroups: comp.ai.neural-nets
From: npchen@bohr.physics.purdue.edu (Nien-Po Chen)
Newsgroups: comp.ai.neural-nets
Subject: a small LCD controlled to a Mac or PC?
Date: 9 Jan 93 00:14:03 GMT
Followup-To: poster
Organization: Purdue University Physics Department

Hi netters,

I am not sure if this is a right group to ask.  If not, sorry about this.

My lab needs a small LCD (diagonal 3" -- 5", like a Sony Watchman TV) as a mask
for some optic experiments.  The pattern on it should be controlled by a 
personal computer like a Mac or a PC.

My first thought is:
1) a commercial product for this purpose -- anybody has the company's info?

2) re-configer a cheap consumer electronic black-&-white Watchman TV or 
   something like that and connect it to the personal computer.  Is there a way
   to have it emulate a computer display?
3) any other idea?

Thank you for your time.
Chen, Nien-Po           npchen@physics.purdue.edu
Jan. 8, 1993

P.S.    Replying to my e-mail address is preferred.
Xref: sparky comp.ai.neural-nets:4772 soc.college.grad:2273
From: fc0v+@andrew.cmu.edu (Franklin Chang)
Newsgroups: comp.ai.neural-nets,soc.college.grad
Subject: Re: Schools strong in neural nets? (was Request: Neural-Nets-classes in US graduate schools)
Date: 9 Jan 93 12:32:35 GMT
Article-I.D.: andrew.QfHp_3G00WBMQ2W3Im
Organization: Sophomore, Math/Computer Science, Carnegie Mellon, Pittsburgh, PA

>	Stanford		Psychology
>	MIT			Brain and Cognitive Sciences
>	UCSD			Cognitive Sciences
>	Carnegie Mellon		Psychology and Computer Science
        Jay McClelland
        Johnathan Cohen
        Mark Johnson
>	Brown			Cognitive and Linguistic Sciences
>	UC Irvine		Computer and Information Sciences
>	Pittsburgh		Psychology and Computer Sciences
>	Boston University	Neural Systems (or something like that)
>	University of CO	Computer Science
>	Oregon Grad Insti	Computer Science
>	Indiana			Psychology and Computer Science

Could people also put down people that are doing neural networks
research in these departments?  I've filled in CMU to the best of my
knowledge.
Thanks,
Frank

 
Newsgroups: comp.ai.neural-nets
From: bouzerda@augean.eleceng.adelaide.edu.AU (Abdesselam Bouzerdoum)
Subject: Postdoc/Research Fellow
Organization: Electrical and Electronic Eng., University of Adelaide
Date: Tue, 5 Jan 1993 06:12:48 GMT

                    POSTDOCTORAL OR RESEARCH FELLOW 
                                   in
                  Signal Processing and Neural Networks
                  **************************************

A postdoctoral or research fellow is sought to join as soon as possible
the Centre for Sensor Signal and Information Processing (CSSIP) and the 
University of Adelaide EE Eng Department. The CSSIP is one of several 
cooperative research centres awarded by the Australian Government to
establish excellence in research and development. The University of 
Adelaide, represented by the EE Eng Dept, is a partner in this cooperative 
research centre, together with the Defence Science and Technology 
Organization (DSTO), four other Universities, and several companies. 
The cooperative research centre consists of more than 50 effective full 
time researchers, and is well equipped with many UNIX Workstations and a 
massively parallel machine (DEC MPP).

The aim is to develop and investigate principles of artificial neural
networks for sensor signal and image processing, classification and
separation of signals, and data fusion. The position is for one year 
with a strong possibility of renewal.

DUTIES: In consultation with task leaders and specialist researchers to
investigate alternative algorithm design approaches, to design experiments
on applications of signal processing and artificial neural networks, to
prepare data and carry out the experiments, to prepare software for testing
algorithms, and to prepare or assist with the prepation of technical reports.

QUALIFICATIONS: The successful candidate must have a Ph.D., a proven 
research record, and a demonstrated ability in written and spoken English.

PAY and CONDITIONS: will be in accordance with University of Adelaide
policies, and will depend on the qualifications and experience.
Appointments may be made in scales A$ 36285 to A$ 41000 for a postdoc, 
and A$ 42538 to A$ 48688 for a research fellow.

ENQUIRIES: Prof. R. E. Bogner, Electrical & Electronic Engineering Dept.,
The University of Adelaide, G.P.O. Box 498, Adelaide, South Australia 5001.
Phone: (61)-08-228-5589,    Fax: (61)-08-232-5720 
Email: bogner@eleceng.adelaide.edu.au

Dr. A. Bouzerdoum, Phone (61)-08-228-5464,   Fax (61)-08-232-5720
Email: bouzerda@eleceng.adelaide.edu.au

Newsgroups: comp.ai.neural-nets
From: cpw@watserv1.uwaterloo.ca
Subject: Is there a data set generator out there?
Organization: University of Waterloo
Date: Thu, 7 Jan 1993 09:07:56 GMT

I hope this isn't a FAQ; I've been out of it for a while.

But I have a desperate need for a good data set generator
which will allow me to generate random vectors with the ranges I want.

This way I can keep my neural networks well-fed and happy.

Please use e-mail. I can't read this group as often as I would like,
but I'll forward this information to anyone who requests it.

Thanks.


Newsgroups: comp.ai.neural-nets
From: erik@til.com (Erik Horstkotte)
Subject: Re: Fuzzy logic
Reply-To: erik@til.com
Organization: Togai InfraLogic, Inc.
Date: Wed, 6 Jan 1993 17:01:23 GMT

In article 11725@cs.sfu.ca, ens@cs.sfu.ca (John Ens) writes:
>Can someone point me to tutorial information (references or ftp
>files) explaining fuzzy logic?

This may be in the FAQ, I'm not sure.

Togai InfraLogic (Yokichi Tanaka and I, actually) runs a publically
accessible fuzzy logic email server that includes, among other
things, a short primer on the mathematics of fuzzy logic, a rather
dated but soon to be updated bibliography on fuzzy logic, and many
documents describing fuzzy applications, etc.  To have a copy of
the help file for the server emailed to you, send an email message
with a subject that is just the word help, and no message body, to
fuzzy-server@til.com.  Alternatively, you can send a message with
no subject, and a one line body with just the word help to the
same address.  If you have any trouble, contact me directly by
email.
---
Erik Horstkotte, Togai InfraLogic, Inc.
The World's Source for Fuzzy Logic Solutions (The company, not me!)
erik@til.com, gordius!til!erik - (714) 975-8522
info@til.com for info, fuzzy-server@til.com for fuzzy mail-server

Newsgroups: comp.ai.neural-nets
From: ra@cs.brown.edu (Ronny Ashar)
Subject: will Cascade Correlation work in stochastic mode?
Organization: Brown University Department of Computer Science
Distribution: comp.ai.neural-nets
Date: Wed, 6 Jan 1993 18:27:26 GMT

Hi

I've been using standard backprop and on-line training, i.e., the algorithm can sample a single randomly generated example at a time. Backprop performs well
when given about 50,000 such examples( thats a small subset of the domain).

However, I would prefer a more robust algorithm. I was looking at Fahlman's 
Cascade Correlation. My impression is that Cascor needs epoch training only;
it could be modified to work in stochastic mode, but, in that case, it will 
end up creating huge nets with redundant units. Is that correct?

Have people been using Cascade Correlation in stochastic mode? I'll appreciate
getting comments/suggestions.

Ronny


Newsgroups: comp.ai.neural-nets
From: starke@rhrk.uni-kl.de (Gerolf J Starke)
Subject: RCS: need help !
Organization: University of Kaiserslautern, Germany
Date: Tue, 5 Jan 1993 09:56:34 GMT


Dear Experts,

I want to work with the newest version of the Rochester
Connectionist Simulator but I cannot install the software.

I tried to install it on a RISC with aix V 3.2: the compiler
needs the ranlib.h file which is not available.

I tried to install it on  a SUN with SUNOS Release 4.0.3: the
compiler needs the Dialog.h, List.h and Text.h files which is
not available.

Is there anyone out there who works with the RCS? Please get in
touch with me.

Thanks for your help in advance.

Gerolf
-- 
Gerolf Joachim Starke                         phone: +49/631/205-2128
Institute of Applied Mechanics                internet: starke@rhrk.uni-kl.de
University of Kaiserslautern, 6750            compuserve: 100010,3451
Germany                                       fax: +49/631/205-3055
Newsgroups: comp.ai.neural-nets
From: peng@aptronix.com (Xiantu Peng)
Subject: Re: Fuzzy logic
Organization: Aptronix Inc
Date: Wed, 6 Jan 1993 01:54:31 GMT

In article <1993Jan5.221130.11725@cs.sfu.ca> ens@cs.sfu.ca (John Ens) writes:
>I thought this would be a FAQ, but I couldn't find the answer
>in the monthly FAQ posting, so here goes...
>
>Can someone point me to tutorial information (references or ftp
>files) explaining fuzzy logic?
>
>Thanks in advance.
>John Ens
>ens@cs.sfu.ca
>


You can logon to a bulletin board system(BBS) called FuzzyNet run by 
Aptronix, Inc. The number is 408-428-1883 and the setting is 8/N/1.
You can download files from the area <News and More..>/Articles. 
Some of the articles available are listed below:

1. Interview with Lotfi Zadeh 
2. Nasa and Fuzzy Logic in Space
3. Fuzzy Logic in Automobiles
4. Crime and Fuzzy Logic
5. The 7 Noble Truths of Fuzzy Logic - by Earl Cox
6. Comparing PID Control to Fuzzy Logic Based Control
7. Fuzzy Logic Consultants
8. Motorola Fuzzy Logic Tutorial - Windows CBT - EXCELLENT
9. Fuzzy logic model for vehicle insurance underwriting
10. A Brief Answer To What is Fuzzy Logic - by Mark Jurik
11. What is FIDE!!!! Full text from the Aptronix Brochure
12. What is Fuzzy Logic and Why Use it
13. Fuzzy Logic 93 -  The First International Conference


Xiantu Peng
peng@aptronix.com
From: xue@masg1.epfl.ch (Xinjian Xue)
Newsgroups: comp.ai.neural-nets
Subject: This has been done?
Keywords: centering design, Kohonen competition
Date: 4 Jan 93 13:44:34 GMT
Organization: Ecole Polytechnique Federale de Lausanne


I am trying to do centering design for electronic network with Kohonen 
competition. Because it is sure that under certain condition (3-dimension,
uniforly distribution), Kohonen competition can geomatrically map the
available perameter space.

My question are:
1. Who has done this research?
2. If someone has done it, where I can find his / her paper?

Thanks.

Xinjian XUE, Dept. of Mathe., EPFL
tel. +41-21-693-2506
e-mail. xue@masg36.epfl.ch
From: khore@solb1.essex.ac.uk (Khor E W)
Newsgroups: comp.ai.neural-nets
Subject: HYBRID SYSTEM
Date: 6 Jan 93 11:40:22 GMT
Reply-To: khore@essex.ac.uk (Khor E W)
Organization: University of Essex, Colchester, UK

I am currently working on a HYBRID system of ANS and ES shell. Could anyone out
there give some pointers? I am also aware of the existence of Expert Network, is it really being used by the industrial. Current state of my work stops at:

ANS
---
i) implemented using C++
ii) extensive use of templates and class
iii) Neurons and connections created as objects to form a concrete network.
iv) readily to interface with any programs using C or C++

ES
---
none so far, but expected to work on a currently available shell. One suggested candidate is CLIPS5 of NASA JSC distributed through COSMIC. It is written in C and highly 'interfacable'.

Any pointers would be appreciated.

E W Khor
Dept of Comp Science, U/G
University of Essex, UK
khore@uk.ac.essex
Newsgroups: comp.ai.neural-nets
From: paulf@manor.demon.co.uk (Paul Fawcett)
Subject: Re: Biologically Plausible Dynamic Artificial Neural Networks 
Distribution: world
Organization: UDI
Reply-To: paulf@manor.demon.co.uk
X-Mailer: Simple NEWS 1.90 (ka9q DIS 1.19)
Date: Sat, 9 Jan 1993 15:52:14 +0000

In article <1993Jan8.191256.28193@news.arc.nasa.gov> doshay@ursa.arc.nasa.gov writes:

>Because M.D. Ross was the first reference in the posting, and I work in her
>lab at NASA Ames, I feel some need to post also. Dr. Ross is a neuroanatomist
>and we study nerves in the vestibular macula at the ultrastructural level. 
>
>First, I have never heard her refer to a DANN in the manner the post does, and
> in
>the post she is referenced right after this acronym.
>

          This was not an appropriate reference. While relevant to the
          article as a whole it is misleading in its context, also the
          acronym was mine.

          Hope this has corrected any confusion.

          Paul.

-- 
--------------------------------------------------------------------------
Paul Fawcett                 |      Internet: paulf@manor.demon.co.uk
London, UK.                  |                tenec@westminster.ac.uk
--------------------------------------------------------------------------
From: choy@skorpio.usask.ca (I am a terminator.)
Newsgroups: comp.ai.neural-nets
Subject: NN to play chess
Date: 8 Jan 1993 20:40:50 GMT
Organization: University of Saskatchewan, Saskatoon, Canada
Distribution: world
NNTP-Posting-Host: skorpio.usask.ca

What training difficulties occur with chess playing neural nets?


-- 

Henry Choy
choy@cs.usask.ca

What rolls down stairs alone or in pairs            This has been brought to 
Rolls over your neighbor's dog?                     you by the numbers 4
What's great for a snack and fits on your back?     and 9 and the letter P.
It's Log, Log, Log!  -- "The Log Song", from            -- Big Bird
                         Ren & Stimpy

Math is tough!       -- Barbie
Newsgroups: comp.ai.neural-nets,soc.college.grad
From: dbrown@newssun.med.miami.edu (Daniel Brown)
Subject: Re: Schools strong in neural nets? (was Request: Neural-Nets-classes in US graduate schools)
Organization: University of Miami, School Of Medicine
Date: Mon, 11 Jan 1993 15:07:26 GMT

In article <QfHp_3G00WBMQ2W3Im@andrew.cmu.edu> fc0v+@andrew.cmu.edu (Franklin Chang) writes:
>>	Stanford		Psychology
				(Rumelhart)

>>	MIT			Brain and Cognitive Sciences
				(Jordan and Poggio)

>>	UCSD			Cognitive Sciences
				(Ellman, Zipser, Sereno, Kirsh, St. John)
				
>>	Carnegie Mellon		Psychology and Computer Science
>        Jay McClelland		(Touretsky)
>        Johnathan Cohen
>        Mark Johnson
>>	Brown			Cognitive and Linguistic Sciences
				(Anderson and Warren)

>>	UC Irvine		Computer and Information Sciences
				(Granger; Lynch in psychobiology)
	
>>	Pittsburgh		Psychology and Computer Sciences
>>	Boston University	Neural Systems (or something like that)
				(Grossberg, Carpenter, many others)

>>	University of CO	Computer Science
				(Smolensky, Mozer)

>>	Oregon Grad Insti	Computer Science

>>	Indiana			Psychology and Computer Science
>
>Could people also put down people that are doing neural networks
>research in these departments?  I've filled in CMU to the best of my
>knowledge.

Dan
From: danz+@CENTRO.SOAR.CS.CMU.EDU (Dan Zhu)
Newsgroups: comp.ai.neural-nets
Subject: some basic questions
Date: 5 Jan 93 17:14:36 GMT
Article-I.D.: cs.C0E58K.KwL.1
Organization: School of Computer Science, Carnegie Mellon
Originator: danz@CENTRO.SOAR.CS.CMU.EDU


  I have some problems with the input and output representation. 

      - Is symmetric sigmoid function (-0.5, 0.5) or (-1, 1) always
        better than the asymmetric one (0, 1)? Any reference? 
      - Shall I do this kind of scaling with the input representation also? 
      - What would be a good cut point to test the network from time to time
        to avoid the overtraining? 
      - I remember I read something like "three layer (with one hidden layer)
        is sufficient for the generalization of the network...". Could anyone
        give me any pointer to the exact reference for it?
      - Also, is there any new reference about the clue for selecting 
        the range of "hidden nodes", "learning rate", "momentum" and 
        judgement about the "initial weight"?

      

      Thanks in advance!


 
    
Newsgroups: comp.ai.neural-nets
From: theodore-michael@yale.edu (Dr. Disorder)
Newsgroups: comp.ai.neural-nets
Subject: Neural-nets and horse racing?
Date: 7 Jan 1993 17:23:10 -0500
Organization: Yale University Science & Engineering UNIX(tm), New Haven, CT 06520-2158
NNTP-Posting-Host: minerva.cis.yale.edu

Yes, I know I'm a moron for even asking this, but that aside, could anyone
point me in the direction of prior research regarding neural-nets and
betting on horses (or just betting generally)? It seems like enough data
is available to train a network to intelligently pick enough winners so that
one would come out ahead (over the long haul).

	Asked with mild embarassment,
		Michael
	

-- 
Practice random acts of randomness.........
		theodore-michael@cs.yale.edu
From: hiwi@fmr.maschinenbau.th-darmstadt.de (Hiwi General Account)
Newsgroups: comp.ai.neural-nets
Subject: RBF calculating confidence intervalls and local training density
Date: 12 Jan 93 12:08:57
Organization: TH-Darmstadt
Distribution: comp
NNTP-Posting-Host: pdv2.fmr.maschinenbau.th-darmstadt.de

Question: RBF calculating confidence intervalls and local training density 

I am looking for RBF-NN (radiar basis functions networks), which are 
able to calculate confidence intervalls of their prediction and
give some information about local training  density.

I`ve already got the article: Using RBF to approximate a function and its 
error bounds by the authors Leonard, Kramer and Ungar, published in IEEE -
Transactions on NN july 1992.

If anybody got some experiences with the above named problem or is 
able to name me some more sources with further information, please let me know.

Thanks so far, 
                 Andreas 


*
* Technical University of Darmstadt 
* Institute for Flight Mechanics and Control Theory
* Petersenstrasse 30
* 6100 Darmstadt (germany)
* Tel:   6151 163090
* FAX:   6151 165434
* Email: hiwi@pdv2.fmr.maschinenbau.th-darmstadt.de
*
Newsgroups: comp.ai.neural-nets