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Neuron Digest Volume 08 Number 10
Neuron Digest Monday, 18 Nov 1991 Volume 8 : Issue 10
Today's Topics:
Announcement of NIPS Bayesian workshop and associated ftp archive
NIPS-91 reminder
post NIPS workshop on speech
Courses and Conference on Neural Networks, May 1992, Boston University
IJCNN'91 Singapore Advanced Program
Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are
available from cattell.psych.upenn.edu (128.91.2.173). Back issues
requested by mail will eventually be sent, but may take a while.
----------------------------------------------------------------------
Subject: Announcement of NIPS Bayesian workshop and associated ftp archive
From: David MacKay <mackay@hope.caltech.edu>
Date: Tue, 05 Nov 91 10:20:59 -0800
One of the two day workshops at Vail this year will be:
`Developments in Bayesian methods for neural networks'
------------------------------------------------------
David MacKay and Steve Nowlan, organizers
The first day of this workshop will be 50% tutorial in content,
reviewing some new ways Bayesian methods may be applied to neural
networks.
The rest of the workshop will be devoted to discussions of
the frontiers and challenges facing Bayesian work in neural networks.
Participants are encouraged to obtain preprints by anonymous ftp
before the workshop. Instructions end this message.
Discussion will be moderated by John Bridle.
Day 1, Morning: Tutorial review.
0 Introduction to Bayesian data modelling. David MacKay
1 E-M, clustering and mixtures. Steve Nowlan
2 Bayesian model comparison and determination of
regularization constants -
application to regression networks. David MacKay
3 The use of mixture decay schemes in backprop
networks. Steve Nowlan
Day 1, Evening: Tutorial continued.
4 The `evidence' framework for classification
networks. David MacKay
Day 1, Evening: Frontier Discussion.
Background:
A:
In many cases the true Bayesian posterior distribution over a hypothesis
or parameter space is difficult to obtain analytically. Monte Carlo
methods may provide a useful and computationally efficient way to estimate
posterior distributions in such cases.
B:
There are many applications where training data is expensive to obtain,
and it is desirable to select training examples so we can learn as much as
possible from each one. This session will discuss approaches for selecting
the next training point "optimally". The same approaches may also be
useful for reducing the size of a large data set by omitting the
uninformative data points.
A Monte Carlo clustering Radford Neal
B Data selection / active query learning Jurgen Schmidhuber
David MacKay
Day 2, morning discussion:
C Prediction of generalisation
Background:
The Bayesian approach to model comparison evaluates
how PROBABLE alternative models are given the data.
In contrast, the real problem is often to estimate
HOW WELL EACH MODEL IS EXPECTED TO GENERALISE.
In this session we will hear about various approaches
to predicting generalisation.
It is hoped that the discussion will shed light on the questions:
- How does Bayesian model comparison relate to generalisation?
- Can we predict generalisation ability of one model assuming
that the `truth' is in a different specified model class?
- Is it possible to predict generalisation ability WITHOUT
making implicit assumptions about the properties
of the `truth'?
- Can we interpret GCV (cross-validation) in terms of prediction
of generalisation?
1 Prediction of generalisation with `GPE' John Moody
2 Prediction of generalisation
- worst + average case analysis David Haussler + Michael Kearns
3 News from the statistical physics front Sara Solla
Day 2, Evening discussion:
(Note: There will probably be time in this final session for continued
discussion from the other sessions.)
D Missing inputs, unlabelled data and discriminative training
Background:
When training a classifier with a data set D_1 = {x,t},
a full probability model is one which assigns a
parameterised probability P(x,t|w). However, many classifiers
only produce a discriminant P(t|x,w), ie they do not model P(x).
Furthermore, classifiers of the first type often yield better
discriminative performance if they are trained as if they were only of
the second type. This is called `discriminative training'. The problem
with discriminative training is that it leaves us with no obvious
way to use UNLABELLED data D_2 = {x}. Such data is usually cheap,
but how can we integrate it with discriminative training?
The same problem arises for most regression or classifier
models when some of the input variables are missing from the input
vector. What is the right thing to do?
1 Introduction: the problem of combining unlabelled
data and discriminative training Steve Renals
2 Combining labelled and unlabelled data
for the modem problem Steve Nowlan
Reading up before the workshop
- ------------------------------
People intending to attend this workshop are encouraged to obtain
preprints of relevant material before NIPS. A selection of preprints
are available by anonymous ftp, as follows:
unix> ftp hope.caltech.edu (or ftp 131.215.4.231)
Name: anonymous
Password: <your name>
ftp> cd pub/mackay
ftp> get README.NIPS
ftp> quit
Then read the file README.NIPS for further information.
Problems? Contact David MacKay, mackay@hope.caltech.edu,
or Steve Nowlan, nowlan@helmholtz.sdsc.edu
- ---------------------------------------------------------------------------
------------------------------
Subject: NIPS-91 reminder
From: John Pearson W343 x2385 <jcp@vaxserv.sarnoff.com>
Date: Thu, 07 Nov 91 13:09:26 -0500
Now's the time to register for the NIPS-91 conference and workshops!
For those of you who don't know about NIPS, read on:
NEURAL INFORMATION PROCESSING SYSTEMS: NATURAL AND SYNTHETIC
Conference: Monday, December 2 - Thursday, December 5, 1991; Denver, Colorado
Workshop: Friday, December 6 - Saturday, December 7, 1991; Vail, Colorado
This is the fifth meeting of an inter-disciplinary conference
which brings together neuroscientists, engineers, computer
scientists, cognitive scientists, physicists, and mathematicians
interested in all aspects of neural processing and computation.
There will be an afternoon of tutorial presentations (Dec 2)
preceding the regular session and two days of focused workshops will
follow at a nearby ski area (Dec 6-7). The meeting is sponsored by the
Institute of Electrical and Electronic Engineers Information Theory
Group, the Society for Neuroscience, and the American Physical
Society.
Plenary, contributed, and poster sessions will be held. There will be
no parallel sessions. The full text of presented papers will be
published. Topical categories include: Neuroscience; Theory;
Implementation and Simulations; Algorithms and Architectures; Cognitive
Science and AI; Visual Processing; Speech and Signal Processing;
Control, Navigation, and Planning; Applications.
The format of the workshop is informal. Beyond reporting on past
research, the goal is to provide a forum for scientists actively
working in the field to freely discuss current issues of concern and
interest. Sessions will meet in the morning and in the afternoon
of both days, with free time in between for the ongoing individual
exchange or outdoor activities. Specific open and/or controversial
issues are encouraged and preferred as workshop topics.
The deadline for submission of abstracts and workshop proposals is May
17th, 1991. For further information concerning the conference contact
Dr. Stephen J. Hanson; NIPS*91 Information; Siemens Research Center;
755 College road East; Princeton NJ, 08540
------------------------------
Subject: post NIPS workshop on speech
From: Uli Bodenhausen <uli@ira.uka.de>
Date: Fri, 08 Nov 91 18:36:02 +0100
- -------------------------------------------------------------------
Optimization of Neural Network Architectures for Speech Recognition
- -------------------------------------------------------------------
Dec. 7, 1991, Vail, Colorado
Uli Bodenhausen, Universitaet Karlsruhe
Alex Waibel, Carnegie Mellon University
A variety of neural network algorithms have recently been applied to
speech recognition tasks. Besides having learning algorithms for
weights, optimization of the network architectures is required to
achieve good performance. Also of critical importance is the
optimization of neural network architectures within hybrid systems
for best performance of the system as a whole.
Parameters that have to be optimized within these constraints include
the number of hidden units,
number of hidden layers,
time-delays,
connectivity within the network,
input windows,
the number of network modules,
number of states
and others. The workshop intends to discuss and evaluate the
importance of these architectural parameters and different integration
strategies for speech recognition systems.
Participants are welcome to present short case studies on the optimization
of neural networks, preferably with an evaluation of the optimization steps.
It would also be nice to hear about some rather unconventional techniques
of optimization (as long as its not vodoo or the 'shake the disk during
compilation' type of technique).
The workshop could also be of interest to researchers working on
constructive/destructive learning algorithms because the relevance of
different architectural parameters should be considered for the design
of these algorithms.
The following speakers have already confirmed their participation:
Kenichi Iso, NEC Corporation, Japan
Patrich Haffner, CNET, France
Mike Franzini, Telefonica I + D, Spain
Allen Gorin, AT&T, USA
Yoshua Bengio, MIT
- -----------------------------------------------------------------------
Further contributions are welcome. Please send mail to uli@ira.uka.de or
uli@speech2.cs.cmu.edu.
- ------------------------------------------------------------------------
------------------------------
Subject: Courses and Conference on Neural Networks, May 1992, Boston University
From: announce@park.bu.edu
Date: Wed, 06 Nov 91 09:58:03 -0500
BOSTON UNIVERSITY
NEURAL NETWORK
COURSES AND CONFERENCE
COURSE 1: INTRODUCTION AND FOUNDATIONS
May 9 - 12, 1992
A systematic introductory course on neural networks.
COURSE 2: RESEARCH AND APPLICATIONS
May 12 - 14, 1992
Eight tutorials on current research and applications.
CONFERENCE: NEURAL NETWORKS FOR
LEARNING, RECOGNITION, AND CONTROL
MAY 14 - 16, 1992
An international research conference presenting INVITED and
CONTRIBUTED papers.
Sponsored by Boston University's Wang Institute,
Center for Adaptive Systems, and
Department of Cognitive and Neural Systems,
with partial support from the
Air Force Office of Scientific Research.
NEURAL NETWORK COURSES
May 9 - 14, 1992
This self-contained, systematic, five-day course is based on the
graduate curriculum in the technology, computation, mathematics, and
biology of neural networks developed at the Center for Adaptive
Systems (CAS) and the Department of Cognitive and Neural Systems
(CNS) at Boston University. This year's curriculum refines and
updates the successful course held at the Wang Institute of Boston
University in May 1990 and 1991. A new two-course format permits
both beginners and researchers to participate. The course
will be taught by CAS/CNS faculty, as well as by distinguished guest
lecturers at the beautiful and superbly equipped campus of the Wang
Institute. An extraordinary range and depth of models, methods, and
applications will be presented. Interaction with the lecturers and
other participants will continue at the daily discussion sessions,
meals, receptions, and coffee breaks that are included with
registration. At the 1990 and 1991 courses, participants came from
many countries and from all parts of the United States.
Course Faculty from Boston University are Stephen Grossberg, Gail
Carpenter, Ennio Mingolla, and Daniel Bullock. Course guest
lecturers are John Daugman, Federico Faggin, Michael I. Jordan, Eric
Schwartz, Alex Waibel, and Allen Waxman.
COURSE 1 SCHEDULE
SATURDAY, MAY 9, 1992
4:00 - 6:00 P.M. Registration
5:00 - 7:00 P.M. Reception
SUNDAY, MAY 10, 1992
Professor Grossberg: Historical Overview, Cooperation and
Competition, Content Addressable Memory, and Associative Learning.
Professors Carpenter and Mingolla: Neocognitron, Perceptrons, and
Introduction to Back Propagation.
Professor Grossberg and Mingolla: Adaptive Pattern Recognition.
MONDAY, MAY 11, 1992
Professor Grossberg: Introduction to Adaptive Resonance Theory.
Professor Carpenter: ART 1, ART 2, and ART 3.
Professors Grossberg and Mingolla: Vision and Image Processing.
Professors Bullock and Grossberg: Adaptive Sensory-Motor Control and
Robotics
TUESDAY, MAY 12, 1992
Professor Bullock and Grossberg: Adaptive Sensory-Motor Control and
Robotics, continued.
Professor Grossberg: Speech Perception and Production, Reinforcement
Learning and Prediction.
End of Course 1 (12:30 P.M.)
COURSE 2 SCHEDULE
TUESDAY, MAY 12, 1992
11:30 A.M. - 1:30 P.M. Registration
Professor Carpenter: Fuzzy Artmap.
Dr. Waxman: Learning 3-D Objects from Temporal Sequences.
WEDNESDAY, MAY 13, 1992
Professor Jordan: Recent Developments in Supervised Learning.
Professor Waibel: Speech Recognition and Understanding.
Professor Grossberg: Vision, Space, and Action.
Professor Daugman: Signal Processing in Neural Networks.
THURSDAY, MAY 14, 1992
Professor Schwartz: Active Vision.
Dr. Faggin: Practical Implementation of Neural Networks.
End of Course 2 (12:30 P.M.)
RESEARCH CONFERENCE
NEURAL NETWORKS FOR LEARNING, RECOGNITION, AND CONTROL
MAY 14-16, 1992
This international research conference on topics of fundamental
importance in science and technology will bring together leading
experts from universities, government, and industry to present their
results on learning, recognition, and control, in invited lectures
and contributed posters. Topics range from cognitive science and
neurobiology through computational modeling to technological
applications.
CALL FOR PAPERS: A featured poster session on neural network
research related to learning, recognition, and control will be held
on May 15, 1992. Attendees who wish to present a poster should
submit three copies of an abstract (one single-spaced page),
postmarked by March 1, 1992, for refereeing. Include a cover letter
giving the name, address, and telephone number of the corresponding
author. Mail to: Poster Session, Neural Networks Conference, Wang
Institute of Boston University, 72 Tyng Road, Tyngsboro, MA 01879.
Authors will be informed of abstract acceptance by March 31, 1992.
A book of lecture and poster abstracts will be given to attendees at
the conference.
CONFERENCE PROGRAM
THURSDAY, MAY 14, 1992
2:00 P.M. - 5:00 P.M. Registration
3:00 P.M. - 5:00 P.M. Reception
Professor Richard Shiffrin, Indiana University: "The Relationship
between Composition/Distribution and Forgetting"
Professor Roger Ratcliff, Northwestern University: "Evaluating
Memory Models"
Professor David Rumelhart, Stanford University: "Learning and
Generalization in a Connectionist Network"
FRIDAY, MAY 15, 1992
Dr. Mortimer Mishkin, National Institute of Mental Health: "Two
Cerebral Memory Systems"
Professor Larry Squire, University of California, San Diego: "Brain
Systems and the Structure of Memory"
Professor Stephen Grossberg, Boston University, "Neural Dynamics of
Adaptively Timed Learning and Memory"
Professor Theodore Berger, University of Pittsburgh: "A Biological
Neural Model for Learning and Memory"
Professor Mark Bear, Brown University: "Mechanisms for Experience-
Dependent Modification of Visual Cortex"
Professor Gail Carpenter, Boston University: "Supervised Learning by
Adaptive Resonance Networks"
Dr. Allen Waxman, MIT Lincoln Laboratory: "Neural Networks for
Mobile Robot Visual Navigation and Conditioning"
Dr. Thomas Caudell, Boeing Company: "The Industrial Application of
Neural Networks to Information Retrieval and Object Recognition
at the Boeing Company"
POSTER SESSION (Three hours)
SATURDAY, MAY 16, 1992
Professor George Cybenko, University of Illinois: "The Impact of
Memory Technology on Neurocomputing"
Professor Eduardo Sontag, Rutgers University: "Some Mathematical
Results on Feedforward Nets: Recognition and Control"
Professor Roger Brockett, Harvard University: "A General Framework
for Learning via Steepest Descent"
Professor Barry Peterson, Northwestern University Medical School:
"Approaches to Modeling a Plastic Vestibulo-ocular Reflex"
Professor Daniel Bullock, Boston University: "Spino-Cerebellar
Cooperation for Skilled Movement Execution"
Dr. James Albus, National Institute of Standards and Technology: "A
System Architecture for Learning, Recognition, and Control"
Professor Kumpati Narendra, Yale University: "Adaptive Control of
Nonlinear Systems Using Neural Networks"
Dr. Robert Pap, Accurate Automation Company: "Neural Network Control
of the NASA Space Shuttle Robot Arm"
Discussion
End of Research Conference (5:30 P.M.)
HOW TO REGISTER:
...To register by telephone, call (508) 649-9731 (x 255)
with VISA or Mastercard between 8:00-5:00 PM (EST).
...To register by fax, complete and fax back the Registration Form
to (508) 649-6926.
...To register by mail, complete the registration form below and
mail it with your payment as directed.
ON-SITE REGISTRATION: Those who wish to register for the courses
and the research conference on-site may do so on a space-available
basis.
SITE: The Wang Institute of Boston University possesses excellent
conference facilities in a beautiful 220-acre setting. It is easily
reached from Boston's Logan Airport and Route 128.
REGISTRATION FORM: NEURAL NETWORKS COURSES AND CONFERENCE
MAY 9-16, 1992
Name: ______________________________________________________________
Title: _____________________________________________________________
Organization: ______________________________________________________
Address: ___________________________________________________________
City: ____________________________ State: __________ Zip: __________
Country: ___________________________________________________________
Telephone: _______________________ FAX: ____________________________
Regular Attendee Full-time Student
Course 1 ( ) $650 N/A
Course 2 ( ) $650 N/A
Courses 1 and 2 ( ) $985 ( )$275*
Conference ( ) $110 ( ) $75*
* Limited number of spaces. Student registrations must be received
by April 15, 1992.
Total payment:______________________________________________________
Form of payment:
( ) Check or money order (payable in U.S. dollars to Boston
University).
( ) VISA ( ) Mastercard
#_________________________________Exp.Date:__________________
Signature (as it appears on card): __________________________
Return to: Neural Networks
Wang Institute of Boston University
72 Tyng Road
Tyngsboro, MA 01879
YOUR REGISTRATION FEE INCLUDES:
COURSES CONFERENCE
Lectures Lectures
Course notebooks Poster session
Evening discussion sessions Book of lecture & poster
Saturday reception abstracts
Continental breakfasts Thursday reception
Lunches Two continental breakfasts
Dinners Two lunches
Coffee breaks One dinner
Coffee breaks
CANCELLATION POLICY: Course fee, less $100, and the research
conference fee, less $60, will be refunded upon receipt of a written
request postmarked before March 31, 1992. After this date no refund
will be made. Registrants who do not attend and who do not cancel
in writing before March 31, 1991 are liable for the full amount of
the registration fee. You must obtain a cancellation number from the
registrar in order to make the cancellation valid.
HOTEL RESERVATIONS:
...Sheraton Tara, Nashua, NH (603) 888-9970, $60/night, plus tax
(single or double).
...Best Western, Nashua, NH (603) 888-1200, $44/night, single, plus
tax, $49/night, double, plus tax.
...Stonehedge Inn, Tyngsboro, MA, (508) 649-4342, $84/night, plus
tax (single or double).
The special conference rate applies only if you mention the name and
dates of the meeting when making the reservation. The hotels in
Nashua are located approximately five miles from the Wang Institute;
shuttle bus service will be provided to them.
AIRLINE DISCOUNTS:
American Airlines is the official airline for Neural Networks.
Receive 45% off full fare with at least seven days advance purchase
or 5% off discount fares. A 35% discount applies on full fare
flights from Canada with an advance purchase of at least seven days.
Call American Airlines Meeting Services Desk at (800) 433-1790 and
be sure to reference STAR#SO252AM. Some restrictions apply.
STUDENT REGISTRATION:
A limited number of spaces at the courses and conference have been
reserved at a subsidized rate for full-time students. These spaces
will be assigned on a first-come, first-served basis. Completed
registration form and payment for students who wish to be considered
for the reduced student rates must be received by April 15, 1992.
------------------------------
Subject: IJCNN'91 Singapore Advanced Program
From: hwang@pierce.ee.washington.edu ( J. N. Hwang)
Date: Sun, 10 Nov 91 11:18:22 -0800
For those of you who didn't receive the Advanced Program
of IJCNN'91 Singapore. Here is a brief summary of the
program.
Jenq-Neng Hwang, Publicity/Technical Committee IJCNN'91
- ----------------------------------------------------------
IJCNN'91 Singapore Preliminary Program Overview:
Sunday, 11/17/91
4:00 pm -- 7:00 pm Registration
Monday, 11/18/91
8:00 am -- 5:30 pm Registration
9:00 am -- 4:00 pm Tutorials
1) Weightless Neural Nets (NNs)
2) Neural Computation: From Brain Research
to Novel Computers
3) Fuzzy Logic & Computational NNs
4) Neural Computing & Pattern Recognition
5) Morphology of Biological Vision
6) Cancelled
7) Successful NN Parallel Computing
8) A Logical Topology of NN
Tuesday, 11/19/91
7:30 am -- 5:30 pm Registration
8:00 am -- 9:00 am Plenary Session (T. Kohonen)
9:15 am -- 12.15 pm Technical Sessions
1) Associative Memory (I)
2) Neurocognition (I)
3) Hybrid Systems (I)
4) Supervised Learning (I)
5) Applications (I)
6) Image Processing/Maths (Poster 1)
1:15 pm -- 3.15 pm Technical Sessions
1) Neurophysiology/Invertebrate
2) Sensation and Perception
3) Hybrid Systems (II)
4) Supervised Learning (II)
5) Applicatiions (II)
6) Supervised Learning (Poster 2)
3:30 pm -- 6:00 pm Technical Sessions
1) Electrical Neurocomputer (I)
2) Image Processing (I)
3) Hybrid Systems (III)
4) Supervised learning (III)
5) Applicatioins (III)
6:00 pm -- 7:30 pm Panel Discussion (G. Deboeck):
Financial Applicatiions of NNs
Wednesday, 11/20/91
7:00 am -- 5:30 pm Registration
8:00 am -- 9:00 am Plenary Session (Y. Nishikawa)
9:15 am -- 12.15 pm Technical Sessions
1) Optimization (I)
2) Image Processing (II)
3) Robotics (I)
4) Supervised Learning (IV)
5) Applications (IV)
6) Applications (Poster 3)
1:15 pm -- 3.15 pm Technical Sessions
1) Mathematical Methods (I)
2) Machine Vision
3) Sensorimotor Control Systems
4) Supervised Learning (V)
5) Applicatiions (V)
6) Robotics (Poster 4)
3:30 pm -- 6:00 pm Technical Sessions
1) Neurocomputer/Associative Memory
2) Neurocognition (II)
3) Unsupervised Learning (II)
4) Supervised Learning (VI)
5) Applicatioins (VI)
5:00 pm -- 6:30 pm Industrial Panel (Tom Caudell)
7:00 pm -- 10:00 pm IJCNN'91 Banquet
Thursday, 11/21/91
7:30 am -- 12:15 pm Registration
8:00 am -- 9:00 am Plenary Session (K. S. Narendra)
9:15 am -- 12.15 pm Technical Sessions
1) Electrical Neurocomputer (II)
2) Neuro-Dynamics (I)
3) Robotics (II)
4) Supervised Learning (VII)
5) Applications (VII)
6) Neurocomputers (Poster 5)
1:15 pm -- 3.15 pm Technical Sessions
1) Associative Memory
2) Mathematical Methods (II)
3) Neuro-Dynamics (II)
4) Supervised/Unsupervised Learning
5) Applicatiions (VIII)
6) Optimization/Associative Memory (Poster 6)
3:30 pm -- 6:00 pm Technical Sessions
1) Optimization (II)
2) Machine Vision (II)
3) mathematical Methods (III)
4) Unsupervised Learning (III)
5) Mathematical Methods/Supervised Learning
Welcome Reception: All speakers, authors, delegates, including students,
and one-day registrants are invited to the "Welcome
Receptiion" on the 18th November. Full details will
included in the Final Program
Conference Registration:
Members Non-Members Students
(no Proc.)
US$ $240 $280 $100 Before 8/31/91
US$ $280 $330 $120 After 8/31/91
US$ $330 $380 $140 On Site
Tutorial Registration: Only for Registered Conference Participants
Registration Fee Per Tutorial
US$ $120 Pre-Register
US$ $140 On Site
US$ $30 Students
Conference Proceedings: Additional copies of the proceedings are available
at the Conference at US$100.00 per set. Rates do not
include postage and handling charges.
Travel Information: Please Contact
TRADEWINDS PTE LTD
77 Robinson Road, #02-06 SIA Building
Singapore 0106
TEL: (65) 322-6845, FAX: (65) 224-1198
Attn: Ms Julie Gan
Banquet Information:
7:00 pm, 20th November 1991
Westin Stamford/Westin Plaza
An excellent 9 course Chinese Dinner will be served
Additional ticket: US$42.00 from IJCNN'91 Secretariat.
------------------------------
End of Neuron Digest [Volume 8 Issue 10]
****************************************
