NetNews Usenet Archive 1992 #27

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Newsgroups: comp.ai.nlang-know-rep Path: sparky!uunet!zaphod.mps.ohio-state.edu!rpi!rpigate!x From: nl-kr-request@cs.rpi.edu (NL-KR Moderator Chris Welty) Subject: NL-KR Digest, Volume 9 No. 60 Message-ID: <199211200132.AA18868@cs.rpi.edu> Reply-To: nl-kr@cs.rpi.edu (NL-KR Digest) Date: Fri, 20 Nov 1992 01:32:18 GMT Approved: nl-kr-request@cs.rpi.edu Lines: 487 NL-KR Digest (Thu Nov 19 14:59:48 1992) Volume 9 No. 60 Today's Topics: Talk: Speech Understanding (Kazunori Muraki at BBN) Program: AI and Stats Workshop Submissions: nl-kr@cs.rpi.edu Requests, policy: nl-kr-request@cs.rpi.edu Back issues are available from host archive.cs.rpi.edu [128.213.3.18] in the files nl-kr/Vxx/Nyy (ie nl-kr/V01/N01 for V1#1), mail requests will not be promptly satisfied. Starting with V9, there is a subject index in the file INDEX. If you can't reach `cs.rpi.edu' you may want to use `turing.cs.rpi.edu' instead. BITNET subscribers: we now have a LISTSERVer for nl-kr. You may send submissions to NL-KR@RPIECS and any listserv-style administrative requests to LISTSERV@RPIECS. ----------------------------------------------------------------- To: nl-kr@cs.rpi.edu Date: Thu, 19 Nov 92 10:55:18 EST From: Helene George <hgeorge@BBN.COM> Subject: Talk: Speech Understanding (Kazunori Muraki at BBN) BBN Science Development Program AI Seminar Series Lecture Kazunori Muraki NEC Corp and EDR, Japan Speech Undestanding and Natural Language Research Activities in NEC BBN, 15/300 70 Fawcett St., Cambridge, MA, 02138 Monday, December 7th, 1992, 10:30am Kazunori Muraki led NEC's pivot-based Machine Translation System in 80's, and is now also a research manager at EDR (Electronic Dictionary Research). He will speak on speech and NL activities at EDR and NEC. Suggestions for AI Seminar speakers are always welcome. Please e-mail suggestions to Dan Cerys (Cerys@bbn.com) or (SBoisen@bbn.com) ------------------------------ To: nl-kr@cs.rpi.edu Newsgroups: news.announce.conferences,comp.ai,comp.ai.nlang-know-rep,... From: wray@ptolemy.arc.nasa.gov (Wray Buntine) Subject: Program: AI and Stats Workshop Nntp-Posting-Host: madonna.arc.nasa.gov Date: Wed, 4 Nov 1992 22:27:40 GMT 2nd Call for Participants and Schedule for Fourth International Workshop on Artificial Intelligence and Statistics January 3-6, 1993 Ft. Lauderdale, Florida PURPOSE: This is the fourth in a series of workshops which has brought together researchers in Artificial Intelligence and in Statistics to discuss problems of mutual interest. The result has been an unqualified success. The exchange has broadened research in both fields and has strongly encouraged interdisciplinary work. This workshop will have as its primary theme: ``Selecting models from data'' FORMAT: Approximately 60 papers by leading researchers in Artificial Intelligence and Statistics have been selected for presentation. To encourage interaction and a broad exchange of ideas, the presentations will be limited to 20 discussion papers in single session meetings over the three days. Focussed poster sessions, each with a short presentation, provide the means for presenting and discussing the remaining 40 research papers. Attendance at the workshop is *not* limited. The three days of research presentations will be preceded by a day of tutorials. These are intended to expose researchers in each field to the methodology used in the other field. LANGUAGE: The language will be English. FORMAT: One day of tutorials and three days of focussed poster sessions, presentations and panels. The presentations are scheduled in the mornings and evenings, leaving the afternoons free for discussions in more relaxed environments. SCHEDULE: Sun: Jan. 3rd. - ------------- Sunday is scheduled for tutorials. There are 4 -- at most two can be attended without conflict. AI for statisticians Morning: Doug Fisher -- Intro. to learning including neural networks Afternoon: Judea Pearl -- Graphical models, causal reasoning, and qualitative decision making. Statistics for AI Morning: Wray Buntine -- Introduction to Statistics and Decision Analysis Afternoon: Daryl Pregibon -- Overview of Statistical Models Mon: Jan. 4th. - -------------- 8:30--10:00 1st. Session---Model Selection Peter Cheeseman--Introduction: "Overview of Model Selection" Beat E. Neuenschwander, Bernard D. Flury, "Principal Components and Model Selection". Cullen Schaffer, "Selecting a Classification Method by Cross-Validation". Stanley Sclove, "Small-Sample and Large-Sample Statistical Model Selection Criteria". - ------------------------------------------------------- 10:00--10:30 break - ------------------------------------------------------- 10:30--12:00 2nd. Session---Model Comparison C. Feng, A. Sutherland, R. King, S. Muggleton, R. Henery, Comparison of Classification Algorithms in Machine Learning, Statistics, and Neural Networks (DRAFT). Richard D. De Veaux, "A Tale of Two Nonparametric Estimation Schemes: MARS and Neural Networks". Christopher de Vaney, "A Support Architecture for Statistical Meta-Information with Knowledge-Based Extensions". + Discussion (speakers and audience) - -------------------------------------------------------- Lunch (provided) - -------------------------------------------------------- 1:30--3:00 1st panel--Alternative Approaches to Model Selection Panel Moderator: Wayne Oldford - -------------------------------------------------------- 3:00--3:30 break - -------------------------------------------------------- 3:30--5:00 3rd. Session---Statistics in AI Nathaniel G. Martin, James F. Allen, "Statistical Probabilities for Planning". Arcot Rajasekar, "On Closures in Knowledge Base Systems". Steffen L. Lauritzen, B. Thiesson, DJ Spiegelhalter, "Diagnostic Systems Created by Model Selection Methods-A Case Study". Vladimir Cherkassky, "Statistical and Neural Network Techniques For Nonparametric Regression". - ------------------------------------------------------- - ------------------------------------------------------- Tue: Jan. 5th. - ------------- 8:30--10:00 4th Session---Causal Models Floriana Esposito, Donato Malerba, Giovanni Semeraro, "Comparison of Statistical Methods for Inferring Causation". J. Pearl and N. Wermuth, "When Do Association Graphs have Causal Explanations". Richard Scheines, "Inferring Causal Structure Among Unmeasured Variables". + Invited speaker - ------------------------------------------------------- 10:00--10:30 break - ------------------------------------------------------- 10:30--12:00 5th Session---Very Short "poster" presentations - ------------------------------------------------------- break--rest of afternoon off - ------------------------------------------------------- 6:00 -7:30 buffet supper (provided) 7:30 -8:40 1st poster session (see list of posters at end) 8:50 -10:00 2nd poster session (preceded by 10 minute changeover) - ------------------------------------------------------- - ------------------------------------------------------- Wed: Jan. 6th. - ------------- 8:30--10:00 6th Session---Influence Diagrams and Probabilistic Networks Remco R Bourckaert, "Conditional Dependence in Probabilistic Networks". Geoffrey Rutledge MD, Ross Shachter, "A Method for the Dynamic Selection of Models Under Time Constraints". Gregory M. Provan, "Diagnosis Over Time Using Temporal Influence Diagrams". + Discussion (speakers and audience) - ------------------------------------------------------- 10:00--10:30 break - ------------------------------------------------------- 10:30--12:00 7th Session---AI in Statistics R. W. Oldford, D. G. Anglin, "Modelling Response Models in Software". D. J. Hand, "Statistical Strategy: Step 1". David Draper, "Assessment and Propagation of Model Uncertainty". Debby Keen, Arcot Rajasekar, "Reasoning With Inductive Dependencies" - -------------------------------------------------------- Lunch (provided) - -------------------------------------------------------- 1:30--3:00 2nd panel 3:00--Business meeting - ----------------------Posters-------------------------------- Russell G. Almond, "An Ontology for Graphical Models". D.L. Banks, R.A. Maxion, "Comparative Evaluation of New Wave Methods for Model Selection". Raj Bhatnagar, Laveen N Kanal, "Models from Data for Various Types of Reasoning". Djamel Bouchaffra, Jacques Rouault, "Different ways of capturing the observations in a nonstationary hidden Markov model: application to the problem of Morphological Ambiguities". Victor L. Brailovsky, "Model selection by perturbing data set (extended abstract)". Carla E. Brodley, Paul Utgoff, "Dynamic Recursive Model Class Selection for Classifier Construction Extended Abstract". W. Buntine, "On Generic Priors in Learning". Paul R. Cohen, "Path Analysis Models of an Autonomous Agent in a Complex Environment". Sally Jo Cunningham, Paul Denize, "A Tool for Model Genertion and Knowledge Acquisition". Luc Devroye, Oliver Kamoun, "Probabilistic Min-Max Trees". E. Diday, P. Brito and E. Mfoumoune, "Modelling Probabilistic Data by Conceptual Pyramidal Clustering". Kris Dockx, James Lutsko, "SA/GA: Survival of the Fittest in Alaska". Zbigniew Duszak, Jerzy Grzymala-Busse, Waldemar W. Koczkoda, "Rule Induction Based on Statistics and Rough Set Theory". J. J. Faraway, "Choise of Order in Regression Strategy". Karina Gibert, "Combining a Knowledge-based System and a Clustering Method For an Inductive Construction of Models". Scott D. Goodwin, Eric Neufeld, Andre Trudel, "Extrapolating Definite Integral Information". Jonathan Gratch, Gerald DeJong, "Rational Learning: Finding a Balance Between Utility and Efficiency". A. K. Gupta, "Information Theoretic Approach to Some Multivariate Tests of Homogeneity". Paula Hietala, "Statistical Reasoning to Enhance User Modelling in Consulting Systems". Adele Howe, Paul R. Cohen, "Detecting and Explaining Dependencies in Execution Traces". Sung-Ho Kim, "On Combining Conditional Influence Diagrams". Willi Klosgen, "Discovery in Databases". G. J. Knafl, A. Semrl, "Software Reliability Expert (SRX)". Bing Leng, Bruce Buchanan, "Using Knowledge-Assisted Discriminant Analysis to Generate New Comparative Terms for Symblic Learner". James F. Lutsko, Bart Kuijpers, "Simulated Annealing in the Construction of Near-Optimal Decision Trees". Yong Ma, David Wilkins, John S. Chandler, "An Extended Bayesian Belief Function Approach to Handle Noise in Inductive Learning". Izhar Matzkevich, Bruce Abramson, "Towards Prior Compromise in Belief Networks (Extended Abstract)". Johnathan Oliver, "Decision Graphs - An Extension of Decision Trees". Egmar Rodel, "A Knowledge Based System for Testing Bivariate Dependence". A.R. Runnaalls, "Global vs Local Sampling Procedures for Inference on Directed Graphs". David Russell, "Statistical Inferencing in a Real-Time Heuristic Controller". Geoffrey Rutledge MD, Ross Shachter, "A Method for the Dynamic Selection of Models Under Time Constraints". Steven Salzberg, David Aha, "Learning to Catch: Applying Nearest Neighbor algorithms to Dynamic Control Tasks". D. Moreira dos Santos, "Selecting a Frailty Model for Longitudinal Breast Cancer Data". Glenn Shafer, "Recursion in Join Trees". P. Shenoy, "Searching For Alternative Representation of Data: A Case for Tetrad". Hidetoshi Shimodaira, "A New Criterion for Selecting Models from Partially Observed Data". P. Smyth, "The Nature of Class Labels in Supervised Learning". Peter Spirtes, Clark Glymour, "Inference, Intervention and Prediction". Marco Valtora, R. Mechling, "PaCCIN: A parallel Constructor of Markov Networks". Aaron Wallack, Ed Nicolson, "Optimal Design of Reflective Sensors Using Probabilistic Analysis". Bradley Whitehall, David Sirag, "Clustering of Smybolically Described Events for Prediction of Numeric Attributes". Nevin Lianwen Zhang, Runping Qi, David Poole, "Minizing Decision Table Sizes in Stepwise-Decomposable Influence Diagrams". Ping Zhang, "On the Choise of Penalty term in Generalized FPE criterion". PROGRAM COMMITTEE: General Chair: R.W. Oldford U. of Waterloo, Canada Programme Chair: P. Cheeseman NASA (Ames), USA Members: W. Buntine NASA (Ames), USA Wm. Dumouchel BBN, USA D.J. Hand Open University, UK W.A. Gale AT&T Bell Labs, USA H. Lenz Free University, Germany D. Lubinsky AT&T Bell Labs, USA M. Deutsch-McLeish U. of Guelph, Canada E. Neufeld U. of Saskatchewan, Canada J. Pearl UCLA, USA D. Pregibon AT&T Bell Labs, USA P. Shenoy U. of Kansas, USA P. Smythe JPL, USA SPONSORS: Society for Artificial Intelligence And Statistics International Association for Statistical Computing REGISTRATION: All fees paid: Before Dec 1, 1992 After Dec 1, 1992 Scientific programme: $225 $275 Full-time Students $135 $175 - Registration fee includes three continental breakfasts and two lunches supplied at the workshop site. - Students must supply proof of full-time student status (at the workshop) to be eligible for reduced rates. A REGISTRATION FORM APPEARS AT THE END OF THIS MESSAGE. TUTORIALS: There are four three hour tutorials planned. Two introducing statistical methodology to AI researchers and two introducing AI methodology to statistical researchers. Before Dec 1, 1992 After Dec 1, 1992 Per Tutorial $65 $75 Full-time Students $40 $45 The tutorials are introductions to the following topics: 1. Learning, including a discussion of neural networks. Speaker: Doug Fisher, Vanderbilt University Orientation: AI for statisticians 2. Graphical models, causal reasoning, and qualitative decision making. Speaker: Judea Pearl, UCLA Orientation: AI for statisticians. 3. Overview of statistical models. Emphasis on generalised linear and additive models. Speaker: Daryl Pregibon, AT&T Bell Labs Orientation: Statistics for AI researchers. 4. Introduction to Statistics. General introduction to statistical topics Speaker: Wray Buntine, NASA Ames Orientation: Statistics for AI researchers. Please indicate which tutorial(s) you are registering for. PAYMENT OF FEES: All workshop fees are payable by cheque or money order in U.S. dollars (drawn on a U.S. bank) to the Society for Artificial Intelligence and Statistics. Send cheque or money order to: R.W. Oldford Chair, 4th Int'l Workshop on A.I. & Stats. Dept. of Statistics & Actuarial Science University of Waterloo Waterloo, Ontario N2L 3G1 CANADA NOTE: ACCOMODATIONS MUST BE ARRANGED DIRECTLY WITH THE HOTEL. ACCOMODATION: We have arranged for a block of rooms to be available to participants at the Workshop site hotel for $85 per night (single or double + tax). Arrangements must be made directly with the hotel. Please mention the Workshop on all communications. Rates are available Jan 1 to Jan 10 (if booked before Dec 17, 1992). Pier 66 Resort and Marina 2301 S.E. 17th Street Causeway Ft. Lauderdale, Florida 33316 (305) 525 6666 (800) 327 3796 (USA only) (800) 432 1956 (Florida only) Fax: (305) 728 3551 Telex: 441-650 REGISTRATION FORM: 4th International Workshop on AI and Statistics January 3-6, 1993 Ft. Lauderdale, Florida Name: _______________________________ Affiliation: _______________________________ Address: _____________________________________________ _____________________________________________ _____________________________________________ _____________________________________________ e-mail: _____________________________________________ Fax: ___________________________ Phone: ___________________________ Scientific Programme Registration ...................... US$___________ Tutorial 1. Learning ................................... US$___________ Tutorial 2. Causal Reasoning ........................... US$___________ Tutorial 3. Statistical Models ......................... US$___________ Tutorial 4. Introduction to Statistics ................. US$___________ _______________________________________________________________________ Total Payment .......................................... US$___________ - - Wray Buntine NASA Ames Research Center phone: (415) 604 3389 Mail Stop 269-2 fax: (415) 604 3594 Moffett Field, CA, 94035 email: wray@kronos.arc.nasa.gov ------------------------------ End of NL-KR Digest *******************