From biehl@physik.uni-wuerzburg.de Mon Oct 14 16:08:09 1996
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From: Michael Biehl <biehl@physik.uni-wuerzburg.de>
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Message-Id: <199610141102.NAA18288@wptx08.physik.uni-wuerzburg.de>
Subject: paper available: Noise Robustness in Multilayer Neural Networks
To: Connectionists <Connectionists@cs.cmu.edu>
Date: Mon, 14 Oct 1996 13:02:29 +0200 (MESZ)
X-Mailer: ELM [version 2.4 PL24 ME8b]
MIME-Version: 1.0
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Content-Transfer-Encoding: 7bit

FTP-host:       ftp.physik.uni-wuerzburg.de 
FTP-filename:   /pub/preprint/1996/WUE-ITP-96-022.ps.gz

The following manuscript is now available via anonymous ftp:
(See below for the retrieval procedure)

------------------------------------------------------------------
    "Noise Robustness in Multilayer Neural Networks"

     M. Copelli, R. Eichhorn, O. Kinouchi, M. Biehl, 
     R. Simonetti, P. Riegler, and N. Caticha

    Ref. WUE-ITP-96-022

                                Abstract
The training of multilayered neural networks in the presence of different types 
of noise is studied. We consider the learning of realizable rules in nonover-
lapping architectures.  Achieving optimal generalization depends on knowledge
of the noise level, however its misestimation may lead to partial or complete loss
of the generalization ability.  We demonstrate this effect in the framework of
online learning and present the results in terms of noise robustness phase
diagrams. While for additive (weight) noise the robustness properties depend on 
the architecture and size of the networks, this is not so for multiplicative 
(output) noise. In this case we find a universal behaviour independent of the 
machine size for both the tree parity and committee machines.     

---------------------------------------------------------------------

Retrieval procedure:

     unix> ftp  ftp.physik.uni-wuerzburg.de
     Name: anonymous  Password: {your e-mail address}
     ftp>  cd pub/preprint/1996
     ftp>  get WUE-ITP-96-022.ps.gz           (*)   
     ftp>  quit
     unix> gunzip WUE-ITP-96-022.ps.gz
e.g. unix> lp WUE-ITP-96-022.ps                     [8 pages]             

(*) can be replaced by "get WUE-ITP-96-022.ps". The file will then
    be uncompressed before transmission (slow!). 
_____________________________________________________________________ 

-- 

Michael Biehl     
Institut fuer Theoretische Physik              
Julius-Maximilians-Universitaet Wuerzburg
Am Hubland
D-97074 Wuerzburg 

email:     biehl@physik.uni-wuerzburg.de
homepage:  http://www.physik.uni-wuerzburg.de/~biehl 
Tel.:      (+49) (0)931 888 5865   
             "      "    "  5131
Fax :      (+49) (0)931 888 5141
From anderson@CS.ColoState.EDU Mon Oct 14 16:08:16 1996
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Date: Mon, 14 Oct 1996 12:36:41 -0600 (MDT)
Message-Id: <199610141836.MAA03873@clapton.cs.colostate.edu>
From: Chuck Anderson <anderson@CS.ColoState.EDU>
To: connectionists@cs.cmu.edu
Subject: research assistantship for Spring, 97

The Department of Computer Science at Colorado State University, Fort
Collins, CO, is looking for a Masters or Ph.D. student to fill a
vacant research assistantship position funded by this NSF project:

National Science Foundation, MIP-9628770, 8/96--7/99, 
 PIs: T. Chen, Electrical Engineering, and A. von Mayrhauser and C. Anderson,
 Computer Science,  "Behavioral Level Design Verifications Using Software
 Testing Techniques and Neural Networks"

We plan to use network inversion and methods from optimal experiment
design to guide the search for test inputs for complex software
systems and hardware models coded in VHDL.  We would like a student
with a strong background in neural networks, experience with compiler
design, and an interest in software and hardware testing.

You can learn more about our department at 

http://www.cs.colostate.edu

and about the PIs' research projects at

http://www.lance.colostate.edu/depts/ee/Profiles/chen.html
http://www.cs.colostate.edu/casi/avm/
http://www.cs.colostate.edu/~anderson

To qualify for this position, you must be accepted into the Computer
Science graduate program at CSU. You may obtain application material
by sending a request via e-mail to gradinfo@cs.colostate.edu.  You may
also send your resume or questions via e-mail to
anderson@cs.colostate.edu.


Chuck Anderson                    anderson@cs.colostate.edu
Department of Computer Science    http://www.cs.colostate.edu/~anderson
Colorado State University         office: 970-491-7491
Fort Collins, CO 80523-1873       FAX:    970-491-2466
From ted@SPENCER.CTAN.YALE.EDU Mon Oct 14 16:08:19 1996
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	id SAA13101; Mon, 14 Oct 1996 18:05:17 GMT
Date: Mon, 14 Oct 1996 18:05:17 GMT
From: ted@SPENCER.CTAN.YALE.EDU
Message-Id: <199610141805.SAA13101@PLANCK.CTAN.YALE.EDU>
To: connectionists@cs.cmu.edu
CC: ted@SPENCER.CTAN.YALE.EDU, ktsai@student.med.harvard.edu,
        hines@SPENCER.CTAN.YALE.EDU
Subject: The Electrotonic Workbench

For those who are concerned with how electrical signals spread in
biological neurons, it may be of interest to learn that Michael
Hines's simulation program NEURON can now compute the electrotonic
transform and display the results as neuromorphic or Log A vs. x
renderings at the click of a button.  An abstract that presents the
basic concepts and illustrates this new feature is at 

http://www.neuron.yale.edu/papers/ebench/ebench.html

Further information about this powerful suite of analytical tools
will be presented at the Society for Neuroscience Meeting in
Washington, DC on Wednesday, Nov. 20, 1996 at 1 PM (Carnevale, N.T.,
Tsai, K.Y., and Hines, M.L..  The Electrotonic Workbench.  Society for
Neuroscience Abstracts 22:1741, 1996, abstract 687.1)


This and other references of interest to those who are concerned with
biologically realistic neural computation are located at

http://www.neuron.yale.edu/papers/nrnrefs.html


--Ted
From dfisher@vuse.vanderbilt.edu Tue Oct 15 02:00:50 1996
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Message-Id: <199610150431.MAA00190@cs.uwa.oz.au>
From: dfisher@vuse.vanderbilt.edu (Douglas H. Fisher)
To: Connectionists@cs.cmu.edu, bayes-news@stat.cmu.edu,
        cogpsy@neuro.psy.soton.ac.uk, colt@cs.uiuc.edu,
        dfisher@vuse.vanderbilt.edu, dietmar@cognition.iig.uni-freiburg.de,
        genetic-programming@cs.stanford.edu, hybrid-list@cs.ua.edu,
        ilpnet@IJS.si, kdd@gte.com, ml@ics.uci.edu, mlnet@swi.psy.uva.nl,
        news-announce-conferences@uunet.uu.net, reinforce@cs.uwa.edu.au,
        sigart@vaxa.isi.edu, uai@maillist.cs.orst.edu
Subject: CFP: 14th International Conference on Machine Learning [connectionists]
Date: Mon, 14 Oct 96 15:36:05 CDT


                Preliminary Call for Papers
 
THE FOURTEENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING
 
                      July 8-12, 1997

                 Nashville, Tennessee, USA
 
The Fourteenth International Conference on Machine Learning 
(ICML-97) will be held at Vanderbilt University in Nashville, 
Tennessee from July 8 to July 12, 1997. ICML-97 is co-located 
with the Tenth Annual Conference on Computational Learning 
Theory (COLT-97), and the organizers anticipate fruitful 
interactions between the two communities. The ICML-97 program
proper includes a half day of tutorials on July 8 (organized 
in conjunction with COLT-97), a technical program that runs 
from July 9 through July 11, and a day of workshops on 
July 12.

Submissions are invited that describe empirical, theoretical,
and cognitive modeling research in all areas of machine 
learning. In addition, papers from related disciplines (e.g.,
information retrieval, statistics, pattern recognition) that 
deal with adaptive intelligence, (semi-)automated knowledge 
acquisition, or (semi-)automated knowledge organization are 
welcome. Submissions that describe the application of machine
learning methods to real-world problems are encouraged, but 
such submissions should speak to general issues of machine
learning, perhaps illustrating novel learning methods or 
demonstrating the utility of established methods in 
previously unexplored settings.

Authors must submit 4 hardcopies of their submissions, as 
well as a copy of their title page via electronic mail. The 
mailing addresses for hardcopies are:

**Regular Mail**                  **Express Mail**
  
Doug Fisher/ICML-97               Doug Fisher/ICML-97
Department of Computer Science    Department of Computer Science
Box 1679, Station B               1500 21st Ave. South
Vanderbilt University             Room 433, Village at Vanderbilt
Nashville, TN 37235 USA           Nashville, TN 37212 USA 
  
                                  615-322-2796 (Express mail forms)

Submissions must arrive by **January 22, 1997.**
Acceptance decisions will be mailed by **March 24, 1997.**
Camera-ready copies will be due by **April 18, 1997.**

A copy of the title page should be sent via electronic mail
to icml97@vuse.vanderbilt.edu by **January 20, 1997** (note 
the date).

The title page should accompany each hardcopy submission, in 
addition to being sent through electronic mail. The title 
page, both the electronic and hardcopy versions, should be 
formatted as follows:

   Title: 

   Author(s) with address(es):

   Abstract (200 word maximum):

   Keywords:

   Email address of contact author:

   Phone number of contact author:

   Multiple submission statement (if applicable):

The title page should be detachable from the main body of the 
paper. The main body should include the paper's title and 
abstract, but not the authors, keywords, or contact 
information.

The main body (excluding detachable title page, but including
everything else such as title, abstract, figures, tables,
and references) of a submission must not exceed **16** pages 
formatted as follows: 12 point font, single-spaced 
(Baselineskip = 0.1875 inches or 0.4763 cm), a maximum 
per-page text width of 5.5 inches (14.00 cm), and a maximum 
per-page text height of 7.5in (19 cm). If the Chair believes 
that a submission exceeds 660 square inches or 4258 square 
centimeters (under 12pt, single space assumptions), then the 
submission will be rejected without review, and an 
explanation will be provided to the author(s). Submissions 
with text on both sides of each page are encouraged.

For complete submission requirements, as well as information 
on registration, housing, workshops, and tutorials, see

   http://cswww.vuse.vanderbilt.edu/~mlccolt/icml97/index.html

or send email to    
 
   icml97@vuse.vanderbilt.edu.

From dwang@cis.ohio-state.edu Tue Oct 15 07:35:30 1996
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From: DeLiang Wang <dwang@cis.ohio-state.edu>
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Date: Mon, 14 Oct 1996 09:43:47 -0400
Message-Id: <199610141343.JAA28477@sarajevo.cis.ohio-state.edu>
To: connectionists@cs.cmu.edu
Subject: Special Issue on Radial Basis Functions Networks
Cc: Y.CAMPFENS@elsevier.nl


                        Call for Papers
       Special Issue on Radial Basis Functions Networks
                for the journal NEUROCOMPUTING
            (http://www.elsevier.nl/locate/neucom)

--------------------------------------------------------------------

One of the most popular neural network architectures due to their fast
learning and broad range of applicability are the Radial Basis Functions (RBF)
Networks. This special issue is dedicated to recent advances in all aspects
of this type of architecture, including but not restricted to:

* theoretical contributions,
* learning methods: supervised, unsupervised, on-line, etc.,
* architectural enhancements,
* applications in signal procession, vision, control, etc.,
* comparative assessments to other neural network architectures.

Submit 6 copies of your manuscript (including keywords, biosketch of all
authors, email address of corresponding author) to:

V. David Sanchez A.
Neurocomputing - Editor in Chief -
Nova Southeastern University
School of Computer and Information Sciences
3100 SW 9th Avenue
Fort Lauderdale, FL 33315
U.S.A.
Fax +1 (954) 723-2744
Email dsanchez@scis.nova.edu

Deadline: 15 December 1996

--------------------------------------------------------------------
From zador@salk.edu Tue Oct 15 17:55:57 1996
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          15 Oct 96 2:18:22 EDT
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Date: Mon, 14 Oct 1996 23:18:19 -0700 (PDT)
From: Tony Zador <zador@salk.edu>
Message-Id: <199610150618.XAA29858@helmholtz.salk.edu>
To: connectionists@cs.cmu.edu
Subject: Re: The Electrotonic Workbench


Neuron is an excellent tool for computing the morphoelectrotonic
transform (MET). However, for those who would prefer to use
Mathematica, a toolkit is available at

    http://mrb.niddk.nih.gov/hagai/publ/Zador95/Abstract.html

Several digitized cortical pyramidal neurons are also available at
this site.

The full published description of the MET can be found in:

   Zador AM; Agmon-Snir H; Segev I.
   The morphoelectrotonic transform: a graphical approach to dendritic
   function.Journal of Neuroscience, 1995 Mar, 15(3 Pt 1):1669-82.

The Mathematica MET Toolkit was used to generate all the figures in
this paper. 

______________________________
Tony Zador 
Salk Institute MNL/S
http://www.sloan.salk.edu/~zador
______________________________


From phkywong@uxmail.ust.hk Tue Oct 15 17:55:59 1996
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From: "Dr. Michael Wong" <phkywong@uxmail.ust.hk>
To: connectionists@cs.cmu.edu
Subject: Paper available
Message-Id: <96Oct15.191239+0800_hkt.102345-24300+615@uxmail.ust.hk>
Date: 	Tue, 15 Oct 1996 19:12:36 +0800

The following paper, to be orally presented at NIPS'96, 
is now available via anonymous FTP. (7 pages)
============================================================================
FTP-host: physics.ust.hk
FTP-files: pub/kymwong/rough.ps.gz

    Microscopic Equations in Rough Energy Landscape for Neural Networks

                        K. Y. Michael Wong
                       Department of Physics, 
         The Hong Kong University of Science and Technology,
                 Clear Water Bay, Kowloon, Hong Kong.
                E-mail address: phkywong@usthk.ust.hk


                               ABSTRACT

We consider the microscopic equations for learning problems in neural networks. 
The aligning fields of an example are obtained from the cavity fields, 
which are the fields if that example were absent in the learning process. 
In a rough energy landscape, 
we assume that the density of the metastable states 
obey an exponential distribution, 
yielding macroscopic properties 
agreeing with the first step replica symmetry breaking solution. 
Iterating the microscopic equations provide a learning algorithm, 
which results in a higher stability than conventional algorithms.

============================================================================
FTP instructions:

unix> ftp physics.ust.hk
Name: anonymous
Password: your full email address
ftp> cd pub/kymwong
ftp> get rough.ps.gz
ftp> quit
unix> gunzip rough.ps.gz
unix> lpr rough.ps (or ghostview rough.ps)
From gordon@aic.nrl.navy.mil Thu Oct 17 09:16:25 1996
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Message-Id: <199610171014.SAA23566@cs.uwa.oz.au>
From: gordon@aic.nrl.navy.mil
To: reinforce@cs.uwa.edu.au
Cc: gordon@aic.nrl.navy.mil
Subject: Call for Workshop Proposals
Date: Wed, 16 Oct 96 11:29:25 EDT


                CALL FOR WORKSHOP PROPOSALS

 Fourteenth International Conference on Machine Learning

                      July 12, 1997


Full and half day workshops will be held on Saturday, July 12, 
1997 following the technical program of the Fourteenth 
International Conference on Machine Learning (ICML-97).  
Workshop proposals are invited in all areas of machine learning. 
Workshop attendees will be required to register for the main ICML-97 
conference. There will be an additional fee for workshop attendance.

Proposals for workshops should be a maximum of three (3) pages
in length, and should contain:

 o A workshop title.
 o A technical description of the workshop and its objectives.
 o An explanation of why the workshop is currently of interest
   to the machine learning community.
 o A description of the workshop format, including invited speakers,
   panels, and discussion sessions.  Please include the length of
   time planned for the workshop and a proposed schedule.
 o A description of the review and paper selection process that
   will be followed.
 o The names, postal and email addresses, and phone numbers of
   the workshop organizers, plus identification of the chair and/or
   key workshop contact.
 o A proposed limit, if any, on workshop attendance.
 o A list of researchers and/or research groups that work in the 
   area and might be interested in attending the proposed workshop 
   (this list need not be included in the 3 page limit).

Please send workshop proposals and related inquiries, preferably 
by electronic mail in plain ASCII text, to:

Diana Gordon
Workshop Chair
EMAIL: gordon@aic.nrl.navy.mil
Naval Research Laboratory, Code 5514
4555 Overlook Avenue, S.W. 
Washington, D.C.  20375-5337 USA

Proposals should be sent as soon as possible, but must be received
by December 4, 1996. Notification of acceptance or rejection will 
be mailed to the organizer by January 6, 1997. Descriptions of 
accepted workshops will be made available via the World-Wide Web (see
address below).  Organizers of accepted workshops will be responsible
for preparing and distributing a Call for Papers and Participation
for their workshops. The ICML-97 Workshops Chair requires a copy of 
each accepted Workshop CFP by January 20, 1997 for display on
the ICML-97 WWW site. The selection of papers, participants, and 
other workshop organizational matters such as the assembly of 
camera-ready copy of the Workshop proceedings are the responsibility 
of the Workshop organizers. ICML-97 will be responsible for local 
arrangements (i.e., rooms, equipment), collection of workshop
registration fees, and printing and delivery of the workshop 
proceedings. ICML-97 will reimburse Workshop organizers
for reasonable and limited costs (e.g., postage for submitting
camera-ready proceedings, copying).


TIMETABLE SUMMARY

Submission of workshop proposals:        December 4, 1996
Notification of acceptance or rejection: January 6, 1997
Accepted workshop CFPs due:              January 20, 1997
Camera-ready proceedings due:            May 28, 1997 (tentative)
Workshops:                               July 12, 1997

--------------------------------------------------------------
More detailed information on the workshops and ICML-97 may be
found at the ICML-97 Web site:

   http://cswww.vuse.vanderbilt.edu/~mlccolt/icml97/index.html

--------------------------------------------------------------

From tgd@chert.CS.ORST.EDU Thu Oct 17 14:14:37 1996
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From: Tom Dietterich <tgd@chert.CS.ORST.EDU>
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To: connectionists@cs.cmu.edu
Subject: Paper available: Statistical Tests for Comparing Supervised Classification Learning Algorithms
Reply-To: tgd@chert.CS.ORST.EDU
Ftp-Host: ftp.cs.orst.edu
Ftp-Filename: /pub/tgd/papers/stats.ps.gz

The following paper is available from
<ftp://ftp.cs.orst.edu/pub/tgd/papers/stats.ps.gz> 

**Hardcopies are not available**

Statistical Tests for Comparing Supervised Classification Learning Algorithms
                         Thomas G. Dietterich
                    Department of Computer Science
                       Oregon State University
                         Corvallis, OR 97331

Abstract:

This paper reviews five statistical tests for determining whether one
learning algorithm out-performs another on a particular learning task.
These tests are compared experimentally to determine their probability
of incorrectly detecting a difference when no difference exists (Type
I error).  Two widely-used statistical tests are shown to have high
probability of Type I error in certain situations and should never be
used.  These tests are (a) a test for the difference of two
proportions and (b) a paired-differences $t$ test based on taking
several random train/test splits.  A third test, a paired-differences
$t$ test based on 10-fold cross-validation, exhibits somewhat elevated
probability of Type I error.  A fourth test, McNemar's test, is shown
to have low Type I error.  The fifth test is a new test, 5x2cv, based
on 5 iterations of 2-fold cross-validation.  Experiments show that
this test also has good Type I error.  The paper also measures the
power (ability to detect algorithm differences when they do exist) of
these tests.  The 5x2cv test is shown to be slightly more powerful
than McNemar's test.  The choice of the best test is determined by the
computational cost of running the learning algorithm.  For algorithms
that can be executed only once, McNemar's test is the only test with
acceptable Type I error.  For algorithms that can be executed ten
times, the 5x2cv test is recommended, because it is slightly more
powerful and because it directly measures variation due to the choice
of training set.

-- 
Thomas G. Dietterich              Voice: 541-737-5559
Department of Computer Science    FAX:   541-737-3014
Dearborn Hall, 303                URL:   http://www.cs.orst.edu/~tgd
Oregon State University
Corvallis, OR 97331-3102
From l.s.smith@cs.stir.ac.uk Thu Oct 17 21:38:03 1996
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Date: Thu, 17 Oct 1996 13:18:36 +0100 (BST)
From: "Dr L S Smith (Staff)" <l.s.smith@cs.stir.ac.uk>
Message-Id: <19961017T121836Z.NAA01062@katrine.cs.stir.ac.uk>
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To: Connectionists@cs.cmu.edu
Subject: CFP: 1st European Workshop on Neuromorphic Systems
Cc: lss@cs.stir.ac.uk

EWNS: 1st European Workshop on Neuromorphic Systems

29-31 August 1997, University of Stirling, Stirling, Scotland

First Call for Papers

Organisers: 


Centre for Cognitive and Computational Neuroscience
University of Stirling, Scotland

and 


Department of Electrical Engineering
University of Edinburgh, Scotland

First Call for Papers

Neuromorphic systems are implementations in silicon of sensory and neural
systems whose architecture and design are based on neurobiology. This
growing area proffers exciting possibilities such as sensory systems which
can compete with human senses and pattern recognition systems that can run
in real-time. The area is at the intersection of many disciplines:
neurophysiology, computer science and electrical engineering.

Papers are requested in the following areas:

Design issues in sensorineural neuromorphic systems: 

auditory, visual, olfactory, proprioception, sensorimotor systems.

Designs for silicon implementations of neural systems.

Papers not exceeding 8 A4 pages are requested: these should be sent to


Dr. Leslie Smith
Department of Computing Science
University of Stirling
Stirling FK9 4LA
Scotland

email: lss@cs.stir.ac.uk
FAX (44) 1786 464551

We also propose to hold a number of discussion sessions on some of the
questions above.  Short position papers (less than 4 pages) are requested.

Key Dates
Submission Deadline: Mon 7th April 1997
Notification of Acceptance: June 2nd 1997

Further information is on the WWW at

http://www.cs.stir.ac.uk/~lss/Neuromorphic/Info1.html
