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- From: neuron-request@cattell.psych.upenn.edu ("Neuron-Digest Moderator")
- Newsgroups: comp.ai.neural-nets
- Subject: Neuron Digest V9 #39 (misc + jobs + papers)
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- Date: 24 Jul 92 02:42:48 GMT
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-
- Neuron Digest Thursday, 23 Jul 1992
- Volume 9 : Issue 39
-
- Today's Topics:
- Administrivia - ND on vacation for over 3 weeks
- NIPS 92 advance program?
- research post in cortical neural networks
- NEURAL NETWORK WORKSHOP
- Call for Papers, Applications of AI (XI)
- IJCNN 92 Beijing Call For Papers *Extension*
- TR - Determining the Number of Hidden Units
-
-
- 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: Administrivia - ND on vacation for over 3 weeks
- From: "N-D Moderator, Peter Marvit" <neuron@cattell.psych.upenn.edu>
- Date: Thu, 23 Jul 92 22:21:08 -0500
-
- Greetings,
-
- As promised, the Neuron Digest Moderator will be goig on vacation for
- about three weeks starting immediately. As a result, the Digest will
- suspend publication with this issue, to resume sometime during the week
- of 17 August. Obviously, no email/correspondence will be answered during
- this time.
-
- This issue is a mix of items which seem somewhat time-sensitive.
- Observant readers will note a lack of paper announcements recently.
- There are some 80 papers in the queue, but they will have to wait until
- after break at which time I will try to send out the backlog.
-
- As always, thanks to you, faithful readers, for making this Digest
- possible and spreading information about Artifical Neural Networks aroudn
- the globe.
-
- -Peter Marvit
- N-D Moderator
-
-
- ------------------------------
-
- Subject: NIPS 92 advance program?
- From: Juan Carlos Guzman <guzman-juan@CS.YALE.EDU>
- Date: Fri, 17 Jul 92 14:18:37 -0500
-
- Hi,
-
- I would like to know where I can find an advance schedule for NIPS'92
- (Neural Information Processing Systems), to be held in Colorado,Nov 30--
- Dec 4, this year. Any leads would be greatly appreciated.
-
- Juan Carlos Guzman.
-
- [[ Editor's Note: I expect we'll see a reasonable version in this Digest
- in September. If someone has earlier information... -PM ]]
-
- ------------------------------
-
- Subject: research post in cortical neural networks
- From: Peter Foldiak <peter@psy.ox.ac.uk>
- Date: Tue, 21 Jul 92 12:15:54 +0000
-
-
- UNIVERSITY OF OXFORD
- DEPARTMENT OF EXPERIMENTAL PSYCHOLOGY
- RESEARCH POST IN CORTICAL NEURAL NETWORKS
-
- Applications are invited for a postdoctoral or graduate position to work
- on the operation of neuronal networks in the brain, with special
- reference to cortical computation. The post available is for a
- theoretician to perform analytic and/or simulation work collaboratively
- with experimental neuroscientists on biologically realistic models of
- computation in cortical structures such as the hippocampus and visual
- cortex. The salary is on the RS1A scale, #12,129-#16,432, and is funded
- by a three-year grant which provides for international collaboration.
- Applications including the names of two referees, or enquiries, to Dr.
- Edmund T. Rolls, University of Oxford, Department of Experimental
- Psychology, South Parks Road, Oxford OX1 3UD, England (telephone
- 0865-271348, e-mail: erolls@vax.ox.ac.uk). The University is an Equal
- Opportunities Employer.
-
-
- Peter Foldiak
-
-
- ------------------------------
-
- Subject: NEURAL NETWORK WORKSHOP
- From: anshu@lexington.rutgers.edu
- Date: Fri, 17 Jul 92 16:32:40 -0500
-
-
-
- NEURAL NETWORK WORKSHOP
-
- 27-29 October, 1992
-
- held at
-
- Ramada Renaissance Hotel, East Brunswick, NJ.
-
- sponsored by
-
- The Aviation Security Research and Development Service of
-
- The Federal Aviation Administration (FAA)
-
- and
-
- CAIP Center, Rutgers University, NJ
-
-
-
- Leaders in the field from academia, industry and government will
- present the state-of-the-art in Neural Network theory and Applications.
- There will be focussed sessions and panels on Neural Networks for vision,
- speech recognition, speaker identification, language acquisition,
- hardware implementations and security systems. Special emphasis will
- be given on the future impact of Neural Networks on Aviation Technology.
-
- The workshop will begin with registration at 8:30 a.m. on Tuesday, 27
- October and end at 4:30 p.m. on Thursday. The $395 registration fee
- ($295 for participants from CAIP member organizations), includes the
- cost of dinners and banquet. Proceedings of the workshop will be
- published in book form.
-
- Registration is limited to 90 participants, including 30 invited
- speakers and panelists. Individuals wishing to attend the workshop
- should register by September 27, 1992.
-
- For further information regarding registration, please contact
-
- Ms. Sandra Epstein
- email: sepstein@caip.rutgers.edu
- Telephone: (908)932-4208
- Fax: (908)932-4775
- Telex: 65-2497820 mci
-
- - ------------------------------------------------------------------------------
-
- NEURAL NETWORK WORKSHOP
-
- 27-29 October, 1992
- |--------------------------------------------------------------------|
- | WORKSHOP REGISTRATION FORM |
- | |
- | YES! I want to attend the Neural Network Workshop, October 27-29, |
- | 1992. I understand my registration fee includes all sessions, |
- | dinners, refreshment breaks, reception and working materials. |
- | |
- | Name ___________________________________________________________ |
- | |
- | Company ________________________________________________________ |
- | |
- | Address ________________________________________________________ |
- | |
- | City/State/Zip _________________________________________________ |
- | |
- | Telephone No. __________________________________________________ |
- | |
- |--------------------------------------------------------------------|
- REGISTRATION IS LIMITED! APPLICATIONS WILL ONLY BE CONSIDERED WHEN
- ACCOMPANIED WITH PAYMENT. MAKE CHECKS PAYABLE TO THE CAIP CENTER,
- RUTGERS UNIVERSITY.
- Registration: Non-member fee ($395) $____________
- Member fee for participants from
- CAIP member organizations ($295) $____________
-
- EARLY REGISTRATION IS ADVISED! Mail form & payment to: CAIP Center,
- Rutgers Univ, 7th floor, CoRE Blgd., PO Box-1390, Piscataway,NJ-08855.
- ...........................................................................
-
- |--------------------------------------------------------------------|
- | HOTEL REGISTRATION FORM |
- | |
- | Name ___________________________________________________________ |
- | |
- | Company ________________________________________________________ |
- | |
- | Address ________________________________________________________ |
- | |
- | Daytime Phone No. ______________________________________________ |
- | |
- | A block of rooms for this conference has been reserved at a special|
- | University room rate of $81 per single/double room per night. |
- | Hotel Reservations will be made through the CAIP Center. |
- | ------------------------------------------------------- |
- | I will require room(s): |
- | Monday, October 26 ( ) |
- | Tuesday, October 27 ( ) |
- | Wednesday, October 28( ) |
- | Thursday, October 29 ( ) |
- |--------------------------------------------------------------------|
-
-
- ------------------------------
-
- Subject: Call for Papers, Applications of AI (XI)
- From: fayyad@ai-cyclops.Jpl.Nasa.Gov (Usama Fayyad)
- Date: Tue, 21 Jul 92 18:11:39 -0800
-
-
- ______________________________________________________________________________
-
- CALL FOR PAPERS 9/14/92 -- CALL FOR PAPERS 9/14/92 -- CALL FOR PAPERS 9/14/92
- ______________________________________________________________________________
-
-
- APPLICATIONS OF AI (XI): Knowledge-Based Systems in Aerospace & Industry
- ------------------------------------------------------------------------
-
- April 12-14, 1993
- Marriott's Orlando World Center
- Resort and Convention Center
- Orlando, Florida, U.S.A.
-
- Sponsored by: SPIE -- The Society for Optical Engineering
- In cooperation with: AAAI -- The American Association for Artificial
- Intelligence
- AIAA -- The American Institute of Aeronautics
- and Astronautics
- IEEE Computer Society
- IEEE Systems, Man, and Cybernetics Society
-
- The Eleventh Applications of Artificial Intelligence Conference will be
- help April 12-14 in Orlando, FL. We invite you to submit a paper by the
- deadline of Sept. 14, 1992. Details of areas and deadlines given below.
-
- Conference Co-Chairs:
- Usama M. Fayyad Ramasamy Uthurusamy
- Jet Propulsion Lab General Motors Research Laboratories
- California Institute of Technology
-
- Program Committee:
-
- Ray Bareiss, Northwestern University
- Steven Lytinen, The University of Michigan
- James Bezdek, University of West Florida
- Stephen C.Y. Lu, University of Illinois
- Gautam Biswas, Vanderbilt University
- Ray Mooney, University of Texas at Austin
- Wray Buntine, NASA Ames Research Center
- Gregory Piatetsky-Shapiro, GTE Laboratories
- Steve Chien, Jet Propulsion Lab
- J. Ross Quinlan, Univ. of Sydney, Australia
- Tharam Dillon, La Trobe Univ., Australia
- Ethan Scarl, Boeing Computer Services
- Richard Doyle, Jet Propulsion Lab
- Jude Shavlik, University of Wisconsin, Madison
- Doug Fisher, Vanderbilt University
- Prakash Shenoy, University of Kansas
- Paul Fishwick, University of Florida
- N.S. Sridharan, Intel Corporation
- David Franke, MCC
- Evangelos Simoudis, Lockheed Aerospace
- Ashok Goel, Georgia Tech.
- Stephen Smith, Carnegie Mellon University
- Larry Hall, University of South Florida
- Jon Sticklen, Michigan State University
- Yumi Iwasaki, Stanford University
- R. Zurawsky, Swinburne Inst. of Tech., Australia
- Ramesh Jain, The University of Michigan
-
-
- This year we will focus on techniques and applications that deal with
- actual industrial and aerospace applications of AI, machine learning, and
- reasoning systems.
-
- Topics of interest include but are not limited to:
-
- 1. Machine Learning
- 2. Industrial and Aerospace Applications
- 3. Diagnostic Systems
- 4. Knowledge Acquisition and Refinement
- 5. Knowledge Based Systems: Verification and Validation
- 6. Manufacturing Systems
- 7. Case-Based Reasoning
- 8. Functional Reasoning
- 9. Model-Based and Qualitative Reasoning
- 10. Multilevel and Integrated Reasoning Systems
- 11. Planning and Scheduling
- 12. Design
- 13. Training and Tutoring Systems
- 14. Intelligent Interfaces and Natural Language Processing
- 15. Intelligent Database Systems
- 16. Parallel Architectures
-
- In addition there will be 2-3 plenary sessions, and one or more panel
- discussions. We also solicit suggestions for special sessions (e.g.,
- Case-Based Tutoring, Reactive Planning in Space Missions). A one-page
- description of such a suggestion should be sent to the Conference Chairs,
- who will then forward it to appropriate members of the Program Committee
- for evaluation. Selection will be based on how well the topic relates to
- the general theme of the conference, and the level of interest it is
- likely to generate.
-
- To submit a paper, send four copies of a complete paper not exceeding 10
- pages single-spaced (approx. 5000 words) including figures and
- bibliography by September 14, 1992 to:
-
- Applications of AI XI: KBS
- SPIE, P.O. Box 10
- 1000 20th Street
- Bellingham, WA 98225.
-
- Tele: (206)-676-3290; Telefax: (206)-647-1445.
-
- Submissions will be reviewed by at least two members of the program
- committee and reviews will be returned to the authors. It is important
- that each paper clearly state the problem which is being addressed, the
- contribution that has been made, and the relation to the current state of
- the art.
-
- The program committee and conference chairs will make a selection of the
- best papers accepted, and these authors will be invited to submit a
- revised version of their paper to one or more special issues of journals
- in AI (to be decided later).
-
- Papers submitted to the Knowledge-Based Systems conference should not
- also be submitted to the Machine Vision and Robotics conference of
- Applications of AI XI. Questions about which conference is most suitable
- for a particular paper should be directed to the program chairmen.
-
- Each presenter is generally allowed 20 to 25 minutes for presentation,
- plus a brief discussion period (about 5 minutes). SPIE will provide the
- following media equipment free of charge: 35 mm carousel slide
- projectors, overhead projectors, electronic pointers and VHS format video
- display.
-
- Author Benefits
- Authors and coauthors who attend the conference will be accorded a
- reduced-rate registration fee, a complimentary one-year non-voting
- membership in SPIE (if never before a member), and other special benefits.
-
- IMPORTANT DATES: PAPERS DUE: September 14, 1992.
- ACCEPT/REJECT LETTERS SENT BY: November 20, 1992
- CAMERA-READY PAPERS (5000 words) DUE: January 18, 1993.
- CONFERENCE DATES: April 12-16, 1993.
-
- Further questions may be directed to (e-mail preferred):
-
- Dr. Usama Fayyad Dr. Ramasamy Uthurusamy
- AI Group M/S 525-3660 Computer Science Department
- Jet Propulsion Lab General Motors Research Labs
- California Institute of Technology 30500 Mound Rd.
- Pasadena, CA 91109 Warren, MI 48090-9055
-
- phone: (818) 306-6197 phone: (313) 986-1989
- fax: (818)-306-6912. fax: (313) 986-9356
- e-mail: Fayyad@aig.jpl.nasa.gov e-mail: Samy@gmr.com
-
- ______________________________________________________________________________
-
- CALL FOR PAPERS 9/14/92 -- CALL FOR PAPERS 9/14/92 -- CALL FOR PAPERS 9/14/92
- ______________________________________________________________________________
-
-
-
- ------------------------------
-
- Subject: IJCNN 92 Beijing Call For Papers *Extension*
- From: Wesley R Elsberry <elsberry@cse.uta.edu>
- Date: Tue, 21 Jul 92 15:09:37 -0600
-
-
-
- IJCNN 92 BEIJING, CHINA
- November 3-6, 1992
-
- CALL FOR PAPERS
-
- --- Extension ---
-
- Papers for the upcoming IJCNN 92 Beijing conference will continue to be
- accepted through July 31, 1992. Papers should be submitted in standard
- IJCNN format (maximum of six pages, etc.) to:
-
- Dr. Harold Szu
- 9402 Wildoak Drive
- Bethesda, MD 20814
-
- Dr. Szu indicates that because of the limited technical communication
- between the rest of the international ANN research community and the
- People's Republic of China, papers submitted may be original work *or*
- review articles.
-
- Researchers are encouraged to contribute on any topic related to
- artificial neural networks.
-
-
- Wesley R. Elsberry
- Sysop, CNS BBS 509-627-6267; Moderator Int'l NEURAL_NET Echo;
- elsberry@cse.uta.edu; POB 1187, Richland, WA 99352; 509-627-3947 voice
-
-
- ------------------------------
-
- Subject: TR - Determining the Number of Hidden Units
- From: Shun-ichi Amari <amari@sat.t.u-tokyo.ac.jp>
- Date: Fri, 17 Jul 92 11:16:33 +0200
-
- The following technical report has been placed in the Neuroprose Archives
- at Ohio State University:
-
- Network Information Criterion ---
- Determining the Number of Hidden Units
- for an Artificial Neural Network Model
-
- Noboru Murata, Shuji Yoshizawa and Shun-ichi Amari
-
- Technical Report METR 92-05, June 1992
- Department of Mathematical Engineering and Information Physics
- University of Tokyo
- Hongo 7-3-1, Bunkyo-ku, Tokyo 113, Japan
-
- SUMMARY: (We recommend typesetting this region by Latex.)
- \documentstyle{article}
- \title{Model selection and effective number of parameters}
- \author{Noboru MURATA \and Shuji YOSHIZAWA \and Shun-ichi AMARI}
-
- \begin{document}
- \maketitle
-
- It is an important problem of the neural computation to select an
- adequate model for a given set of training data. This problem
- naturally leads us a generalization of the AIC criterion of the model
- selection of statistical models (see Murata et al. [1991], Moody
- [1992]). The present note points out a natural generalization of the
- AIC criterion, showing that the results of the above two papers are
- equivalent and that they are applicable to more general situations.
-
- Let us consider a stochastic neural network, parameterized by a set of
- $m$ weights $\theta=(\theta^1,\cdots,\theta^m)$, whose input-output
- behavior is specified by a conditional probability $p(y|x,\theta)$,
- namely the probability distribution of output $y$ when the input
- signal is $x$ (the signal $x$ might be multi dimensional). Let
- $q(y|x)$ be the true probability from which $n$ examples
- $(y_i,x_i)$,$(i=1,\cdots,n)$ are generated, where $x_i$ is generated
- from an unknown probability distribution $q(x)$ independently. We
- define a sample $\Xi_t=\{(y_i,x_i); i=1,\cdots,t\}$ as a set of $t$
- examples. The main problem is to find the best candidate $\theta^*$
- which approximates the conditional distribution $q(y|x)$ and to
- evaluate the model ability, where there might not exist $\hat\theta$
- such that $p(y|x,\hat\theta)=q(y|x)$.
-
- We use a test criterion
- \begin{displaymath}
- D(q,p(\theta))=K[q:p(\theta)]+S(\theta)
- \end{displaymath}
- to be minimized, where $K[q:p(w)]$ represents a general divergence
- measure between two conditional probabilities $q$ and $p(\theta)$, and
- $S(\theta)$ is a regularization term which restricts the parameter
- $\theta$ within an appropriate area (Moody [1992]). We give two
- typical case of $K$. One is the Kullback-Leibler divergence
- \begin{displaymath}
- K[q:p(\theta)]=\int q(x)q(y|x)\log{\frac{q(y|x)}{p(y|x,\theta)}}dydx,
- \end{displaymath}
- and the other is the squared error
- \begin{displaymath}
- K[q:p(\theta)]=\int\|y-f(x,\theta)\|^2q(x)q(y|x)dydx,
- \end{displaymath}
- where
- \begin{displaymath}
- f(x,\theta)=\int y\ p(y|x,\theta)dy.
- \end{displaymath}
- Any divergence measure of the type
- \begin{displaymath}
- K[q:p(\theta)]=\int q(x)q(y|x)k(x,y;\theta)dydx
- \end{displaymath}
- works well.
-
- Given the sample $\Xi_t$, we search for the best parameter $\theta^*$
- that minimize
- \begin{displaymath}
- D(q^*,p(\theta))=K[q^*:p(\theta)]+S(\theta),
- \end{displaymath}
- where $q^*$ is the empirical distribution given by the sample $\Xi_t$,
- that is,
- \begin{displaymath}
- K[q^*:p(\theta)]=\frac{1}{t}\sum_{i=1}^{t} k(x_i,y_i;\theta).
- \end{displaymath}
- This is because the true distributions $q(x)$ and $q(y|x)$ are
- unknown, so we substitute the empirical distribution for the true
- joint distribution $q(x)q(y|x)$. The minimized $D(q^*,p(\theta^*))$ is
- called the training loss or the training error, and it can be used for
- estimating the test loss or the generalization error $D(q,p(\theta^*))$,
- which shows the averaged behavior of the trained network when a new
- example is given.
-
- Since these quantities depend on the sample $\Xi_t$ whose elements are
- chosen randomly, we take the expectation $\langle\cdot\rangle$ with respect to
- the sample $\Xi_t$. We can the prove the following relation
- \begin{displaymath}
- \langle D(q,p(\theta^*))\rangle=\langle D(q^*,p(\theta^*))\rangle
- +\frac{1}{t}\mbox{\rm tr}GQ^{-1}+\frac{1}{\sqrt{t}}U,
- \end{displaymath}
- where $U$ is an unbiased random value of order $1$, common to all the
- models which have the same architecture, $G$ is the covariance matrix
- of $\nabla\{k(x,y;\theta^*)+S(\theta^*)\}$ and $Q$ is the Hessian
- matrix of $D(q,p(\theta^*)$. These quantities are to be evaluated by
- using the empirical distribution $q^*$ instead of the true but unknown
- $q(x)$ and $q(y|x)$. When we compare the abilities of two different
- models and chose better model, we can use a quantity
- \begin{displaymath}
- D(q^*,p(\theta^*))+\frac{1}{t}\mbox{\rm tr}GQ^{-1},
- \end{displaymath}
- and select one model whose value of the quantity is smaller than the
- other's.
-
- Now we can compare this result with others. If the probability
- distribution is unconditional, $K$ is the Kullback-Leibler divergence,
- $D$ includes no regularization term (S(w)=0), and there exist $\hat\theta$
- such that $q=p(\hat\theta)$, then $Q$ and $G$ coincide with the Fisher
- information matrix and
- \begin{displaymath}
- m^*=\mbox{\rm tr}GQ^{-1}=m,
- \end{displaymath}
- holds, where $m$ is the dimension number of the parameter $\theta$.
- This is the classic AIC result. When no such $\hat\theta$ exists, $G$
- and $Q$ never coincide with the Fisher information matrix (Takeuchi
- [1980]), and an effective dimension $m^*$ is different from $m$. When
- $q$ and the optimal $p$ is close, Amari [1980] calculated $m^*$ by
- using an ancillary statistics and the $m$-curvature of the model
- surface.
-
- A sketch of the proof of the present result was given in Murata et al.
- [1991], where the regularization term is not taken into account but
- the proof remains valid. Moody [1992] defined the effective dimension
- by
- \begin{displaymath}
- m^*=\mbox{\rm tr}(TQ^{-1}T^T),
- \end{displaymath}
- where
- \begin{displaymath}
- G=T^TT
- \end{displaymath}
- holds, so that it coincides with the above result. It should be noted
- that the above result holds without assuming the linearity of the
- model, existence of $\hat\theta$, the additive noise $\xi$ of the form
- of
- \begin{displaymath}
- z=f(x,w)+\xi,
- \end{displaymath}
- etc. Therefore, the result of Moody holds under another framework and
- the AIC criterion can be applied in a general non-linear model.
-
- On the other hand, it should be emphasized that this generalized criterion
- cannot be used when we compare two models of different architectures,
- say a neural network model and a radial basis expansion model.
- This is because the quantity $U$ of the order $1/\sqrt{t}$ term is common
- only for two models in which one model is included in the other as a submodel.
- The AIC criterion is valid only for such a family of models of submodels.
- This important remark should more clearly be recognized,
- since it is not clearly written in the original AIC theory.
- \end{document}
-
- END OF SUMMARY
-
- ***** HOW TO OBTAIN A COPY *****
-
- a) Via FTP:
-
- unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
- Name: anonymous
- Password: (type your E-mail address)
- ftp> cd pub/neuroprose
- ftp> binary
- ftp> get murata.nic.ps.Z
- ftp> quit
- unix> uncompress murata.nic.ps.Z
- unix> lpr murata.nic.ps
-
- b) Via postal mail:
-
- Request
-
- Noboru Murata,
- Department of Mathematical Engineering and Information Physics
- University of Tokyo
- Hongo 7-3-1, Bunkyo-ku, Tokyo 113
- Japan.
-
- or E-mail: mura@sat.t.u-tokyo.ac.jp
-
-
- ------------------------------
-
- End of Neuron Digest [Volume 9 Issue 39]
- ****************************************
-