Article: 1240 of comp.theory.cell-automata Newsgroups: comp.theory.cell-automata Path: lirmm!ws41.cnusc.fr!univ-lyon1.fr!centre.univ-orleans.fr!jussieu.fr!oleane!pipex!howland.reston.ans.net!swrinde!sgiblab!cs.uoregon.edu!reuter.cse.ogi.edu!netnews.nwnet.net!serval.net.wsu.edu!corsair.eecs.wsu.edu!schlimme From: Jeffrey C. Schlimmer Subject: Machine Learning Conference Message-ID: X-Xxmessage-Id: X-Xxdate: Mon, 3 Oct 94 00:05:47 GMT Sender: news@serval.net.wsu.edu (News) Organization: Washington State University X-Useragent: Version 1.1.3 Date: Tue, 4 Oct 1994 00:05:52 GMT Lines: 109 PRELIMINARY CALL FOR PAPERS Twelfth International Conference on Machine Learning Tahoe City, California July 9-12, 1995 The Twelfth International Conference on Machine Learning (ML95) will be held at the Granlibakken Resort in Tahoe City, California during July 9-12, 1995, with informal workshops on July 9. We invite paper submissions from researchers in all areas of machine learning. The conference will include presentations of refereed papers and invited talks. REVIEW CRITERIA Each submitted paper will be reviewed by at least two members of the program committee and will be judged on significance, originality, and clarity. Papers submitted simultaneously to other conferences must clearly state so on the title page. PAPER FORMAT Submissions must be clearly legible, with good quality print. Papers are limited to a total of twelve (12) pages, EXCLUDING title page and bibliography, but INCLUDING all tables and figures. Papers must be printed on 8-1/2 x 11 inch paper or A4 paper using 12 point type (10 characters per inch) with no more than 38 lines per page and 75 characters per line (e.g., LaTeX 12 point article style). The title page must include an abstract and email and postal addresses of all authors. Papers without this format will not be reviewed. To save paper and postage costs please use DOUBLE-SIDED printing. REQUIREMENTS FOR SUBMISSION Send four (4) copies of each submitted paper to one of the conference co-chairs. Papers must be received by FEBRUARY 7, 1995 . Electronic or FAX submissions are not acceptable. Notification of acceptance or rejection will be mailed to the first (or designated) author by March 22, 1995. Camera-ready accepted papers are due on April 25, 1995. INFORMAL WORKSHOPS Proposals for informal workshops are invited in all areas of machine learning. Send a two (2) page description of the proposed workshop, its objectives, organizer(s), and expected number of attendees to the workshop chair. Proposals must be received by DECEMBER 1, 1994. Conference Co-Chairs Armand Prieditis Department of Computer Science University of California Davis, CA 95616 priediti@cs.ucdavis.edu Stuart Russell Computer Science Division University of California Berkeley, CA 94720 russell@cs.berkeley.edu Program Committee (To Be Announced). Workshop Chair Sridhar Mahadevan Department of Computer Science and Engineering University of Southern Florida 4202 East Fowler Avenue, EBG 118 Tampa, Florida 33620 mahadeva@csee.usf.edu Publicity Chair Jeff Schlimmer School of Electrical Engineering and Computer Science Washington State University Pullman, WA 99164-2752 schlimme@eecs.wsu.edu http://www.eecs.wsu.edu/~schlimme Local Arrangements Debbie Chadwick Department of Computer Science University of California Davis, CA 95616 chadwick@cs.ucdavis.edu GENERAL INQUIRIES Please send general inquiries to ml95@cs.ucdavis.edu . To receive future conference announcements please send a note to the publicity chair. Current conference information available online on the World-Wide Web as http://www.eecs.wsu.edu/~schlimme/ml95.html . 5.1 Twelfth International Conference on Machine Lear ning quiniou@irisa.fr (Rene Quiniou) Fri, 19 May 1995 16:56:06 +0200 SCHEDULE Twelfth International Conference on Machine Learning Granlibakken Resort, Tahoe City, California, U.S.A. July 9-12, 1995 MONDAY, JULY 10 8.45 - 9.00 Welcome address 9.00 - 10.00 Invited speaker introduced by M. Jordan David Heckerman, Microsoft Research, "Machine Learning and Uncertainty in AI 10.00 - 10.30 Break 10.30 - 12.00 Plenary session chaired by T. Dietterich "Horizontal Generalization", David H. Wolpert (Santa Fe Institute, USA) "TD Models: Modeling the World at a Mixture of Time Scales", Richard S. Sutton (USA) "Learning Policies for Partially Observable Environments: Scaling Up", Michael L. Littman, Anthony R. Cassandra, Leslie P. Kaelbling (Brown U., USA) 12.00 - 1.30 Lunch 1.30 - 3.30 Parallel sessions Track 1 chaired by A. Moore "Optimal Adaptive Disk Spindown via Rent-to-Buy in Probabilistic Environments", P. Krishnan, Philip M. Long, Jeffrey Scott Vitter (Duke U., USA) "Free to Choose: Investigating the Sample Complexity of Active Learning of Real-Valued Functions", Partha Niyogi (Massachusetts Institute of Technology, USA) "Active Exploration and Learning in Real-Valued Spaces using Multi-Armed Bandit Allocation Indices", Marcos Salganicoff (U. of Delaware, USA), Lyle H. Ungar (U. of Pennsylvania, USA) "Q-Learning for Bandit Problems", Michael Duff (U. of Massachusetts, Amherst, USA) Track 2 chaired by W. Buntine "On Pruning and Averaging Decision Trees", Jonathan J. Oliver (Monash U., Australia) "Retrofitting Decision Tree Classifiers using Kernel Density Estimation", Padhraic Smyth, Alex Gray, Usama M. Fayyad (Jet Propulsion Laboratory, USA) "Automatic Selection of Split Criterion during Tree Growing Based on Node Location", Carla E. Brodley (Purdue U., USA) Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves", David Lubinsky (U. of Witwatersrand, South Africa) Track 3 chaired by S. Kasif "For Every Generalization Action, Is There an Equal and Opposite Reaction?", R. Bharat Rao (Siemens Corporate Research, USA), Diana Gordon, William Spears (Naval Research Laboratory, USA) Error-Correcting Output Coding Corrects Bias and Variance, Eun Bae Kong, Thomas G. Dietterich (Oregon State U., USA) "A Bayesian Analysis of Algorithms for Learning Finite Functions", James Cussens (Glasgow Caledonian U., Scotland) "Automatic Parameter Selection by Minimizing Estimated Error", Ron Kohavi, George H. John (Stanford U., USA) 3.30 - 4.00 Break 4.00 - 5.30 Parallel sessions Track 1 chaired by S. Mahadevan Efficient Memory-Based Dynamic Programming", Jing Peng (U. of California, Riverside, USA) Efficient Learning from Delayed Rewards through Symbiotic Evolution", David E. Moriarty, Risto Miikkulainen (U. of Texas at Austin, USA) Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State, R. Andrew McCallum (U. of Rochester, USA) Track 2 chaired by U. Fayyad "Learning Prototypical Concept Descriptions", Piew Datta, Dennis Kibler (U. of California, Irvine, USA) "K*: An Instance-Based Learner Using an Entropic Distance Measure, John G. Cleary, Leonard E. Trigg (U. of Waikato, New Zealand) "Bounds on the Classification Error of the Nearest Neighbor Rule, John A. Drakopoulos (Stanford U., USA) Track 3 chaired by K. Yamanishi "A Comparison of Induction Algorithms for Selective and Non-Selective Bayesian Classifiers", Moninder Singh (U. of Pennsylvania, USA), Gregory M. Provan (Institute for Decision Systems Research, USA) "Hill Climbing Beats Genetic Search on a Boolean Circuit Synthesis Problem of Koz a s", Kevin Lang (NEC Research Institute, USA) "Symbiosis in Multimodal Concept Learning", Jukka Hekanaho (Abo Akademi U., Finland) 6.00 - 7.30 Reception TUESDAY, JULY 11 8.30 - 9.30 Invited speaker introduced by L. Kaelbling Dean Pomerleau, CMU, "Machine Learning for Autonomous Driving and Collision Warning" 9.30 - 10.00 Plenary session chaired by L. Kaelbling Explanation-Based Learning and Reinforcement Learning: A Unified View", Thomas G. Dietterich (Oregon State U., USA), Nicholas S. Flann (Utah State U., USA) 10.00 - 10.30 Break 10.30 - 12.00 Plenary session chaired by R. Greiner "Theory and Applications of Agnostic PAC-Learning with Small Decision Trees", Peter Auer (U. of California, Santa Cruz, USA), Wolfgang Maass (T.U Graz, Austria), Robert Holte (U. of Ottawa, Canada) "Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain", Avrim Blum (Carnegie Mellon U., USA) "Fast Effective Rule Induction", William W. Cohen (AT&T Bell Laboratories, USA) 12.00 - 1.30 Lunch 1.30 - 3.30 Parallel sessions Track 1 chaired by J. Dejong "Case-Based Acquisition of Place Knowledge, Pat Langley (Institute for the Study of Learning and Expertise, USA), Karl Pfleger (Stanford U., USA) "A Case Study of Explanation-Based Control", Gerald DeJong (U. of Illinois at Urbana-Champaign, USA) "Learning by Observation and Practice: An Incremental Approach for Planning Operator Acquisition", Xuemei Wang (Carnegie Mellon U., USA) Inductive Learning of Reactive Action Models", Scott Benson (Stanford U., USA) Track 2 chaired by J. Catlett "Compression-Based Discretization of Continuous Attributes", Bernhard Pfahringer (Austrian Research Institute for AI, Austria) "MDL and Categorical Theories (Continued)", J.R. Quinlan (U. of Sydney, Australia) "Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability", Jurgen Schmidhuber (IDSIA, Lugano, Switzerland) Inferring Reduced Ordered Decision Graphs of Minimal Description Length", Arlindo Oliveira (INESC, Lisboa, Portugal), Alberto Sangiovanni-Vincentelli (U. of California, Berkeley, USA) Track 3 chaired by R. Mooney "A Linguistically-Based Semantic Bias for Theory Revision", Clifford Brunk, Michael Pazzani (U. of California, Irvine, USA) "The Challenge of Revising an Impure Theory", Russell Greiner (Siemens Corporate Research, USA) "Lessons from Theory Revision Applied to Constructive Induction", Steven K. Donoho, Larry Rendell (U. of Illinois at Urbana-Champaign, USA) "Protein Folding: Symbolic Refinement Competes with Neural Networks", Susan Craw, Paul Hutton (Robert Gordon U., Scotland) 3.30 - 4.00 Break 4.00 - 5.30 Parallel sessions Track 1 chaired by K. Yamanishi "A Reinforcement Learning by Stochastic Hill Climbing on Discounted Reward", Hajime Kimura, Masayuki Yamamura, Shigenobu Kobayashi (Tokyo Institute of Technology, Japan) "Fast and Efficient Reinforcement Learning with Truncated Temporal Differences", Pawel Cichosz, Jan J. Mulawka (Warsaw U. of Technology, Poland) "A Cooperative Q-Learning Approach to the Traveling Salesman Problem", Luca Maria Gambardella (IDSIA, Lugano, Switzerland), Marco Dorigo (Universite Libre de Bruxelles, Belgium) Track 2 chaired by P. Tadepalli "A Comparative Evaluation of Voting and Meta-Learning on Partitioned Data", Philip K. Chan, Salvatore J. Stolfo (Columbia U., USA) "Learning with Small Disjuncts", Gary M. Weiss (Rutgers, USA) "On Handling Tree-Structured Attributes in Decision Tree Learning", Hussein Almuallim, Yasuhiro Akiba, Shigeo Kaneda (NTT Communication Science Laboratories, Japan) Track 3 chaired by L. Hellerstein "Comparing Several Linear-Threshold Learning Algorithms on Tasks Involving Superfluous Attributes", Nick Littlestone (NEC Research Institute, USA) Efficient Learning with Virtual Threshold Gates", Wolfgang Maass (T.U Graz, Austria), Manfred K. Warmuth (U. of California, Santa Cruz, USA) "A Quantitative Study of Hypothesis Selection", Philip W. L. Fong (U. of Waterloo, Canada) TBA Banquet at High Camp, Squaw Valley WEDNESDAY, JULY 12 8.30 - 9.30 Invited speaker introduced by C. Cardie Bruce Croft, U. Massachusetts at Amherst, "Machine Learning and Information Retrieval" 9.30 - 10.00 Plenary session chaired by R. Sutton "Removing the Genetics from the Standard Genetic Algorithm", Shumeet Baluja, Rich Caruana (Carnegie Mellon U., USA) 10.00 - 10.30 Break 10.30 - 12.00 Plenary session chaired by S. Thrun "Residual Algorithms: Reinforcement Learning with Function Approximation", Leemon Baird (US Air Force Academy, USA) "Stable Function Approximation in Dynamic Programming", Geoffrey Gordon (Carnegie Mellon U., USA) "NewsWeeder: Learning to Filter News", Ken Lang (Carnegie Mellon U., USA) 12.00 - 1.30 Lunch 1.30 - 3.00 Parallel sessions Track 1 chaired by M. Pazzani "An Inductive Learning Approach to Prognostic Prediction", W. Nick Street, O. L. Mangasarian, W. H. Wolberg (U. of Wisconsin, USA) "Distilling Reliable Information from Unreliable Theories", Sean P. Engelson, Moshe Koppel (Bar-Ilan U., Israel) Using Multidimensional Projections to Find Relations", Eduardo Perez, Larry Rendell (U. of Illinois at Urbana-Champaign, USA) Track 2 chaired by C. Cardie "Tracking the Best Expert", Mark Herbster, Manfred K. Warmuth (U. of California, Santa Cruz, USA) "On Learning Decision Committees", Richard Nock, Olivier Gascuel (LIRMM, Montpellier, France) "Committee-Based Sampling for Training Probabilistic Classifiers", Ido Dagan, Sean P. Engelson (Bar-Ilan U., Israel) Track 3 chaired by I. Bratko "Automatic Speaker Recognition: An Application of Machine Learning", Brett Squires, Claude Sammut (U. of New South Wales, Australia) "Learning Collection Fusion Strategies for Information Retrieval", Geoffrey Towell, Ellen M. Voorhees, Narendra K. Gupta, Ben Johnson-Laird (Siemens Corporate Research, USA) "Text Categorization and Relational Learning", William W. Cohen (AT&T Bell Laboratories, USA) 3.00 - 3.30 Break 3.30 - 4.30 Parallel sessions Track 1 chaired by D. Wilkins "Learning Proof Heuristics by Adapting Parameters", Matthias Fuchs (U. Kaiserslautern, Germany) "Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network", Justine Blackmore, Risto Miikkulainen (U. of Texas at Austin, USA) Track 2 chaired by C. Schaffer Efficient Algorithms for Finding Multi-Way Splits for Decision Trees", Thruxton Fulton, Simon Kasif, Steven Salzberg (Johns Hopkins U., USA) "Supervised and Unsupervised Discretization of Continuous Features", James Dougherty, Ron Kohavi, Mehran Sahami (Stanford U., USA) Track 3 chaired by C. Cardie "Learning Hierarchies from Ambiguous Natural Language Data", Takefumi Yamazaki (NTT Communication Science Laboratories, Japan), Michael J. Pazzani, Christopher Merz (U. of California, Irvine, USA) "On-Line Learning of Semantic Knowledge using Multi-Dimensional Weighted Majority Algorithms", Naoki Abe, Hang Li, Atsuyoshi Nakamura (NEC C&C Research Laboratories, Japan) 4.30 - 5.00 Business meeting http://www.eecs.wsu.edu/ schlimme/ml95.html 15