Copy Link
Add to Bookmark
Report
NL-KR Digest Volume 14 No. 34
NL-KR Digest Mon May 29 23:23:34 PDT 1995 Volume 14 No. 34
Today's Topics:
Program: ML12 Machine Learning, Jul 95, Tahoe City
* * *
Subcriptions: listserv-style administrative requests to
nl-kr-request@ai.sunnyside.com.
Submissions, policy, questions: nl-kr@ai.sunnyside.com
To speed up processing of your submission write to
listserv@ai.sunnyside.com with the message:
GET nl-kr style
Back issues:
FTP: ai.sunnyside.com:/pub/nl-kr/Vxx/Nyyy
/pub/nl-kr/Vxx/INDEX
Gopher: ai.sunnyside.com, Port 70, in directory /pub/nl-kr
Email: write to LISTSERV@AI.SUNNYSIDE.COM, omit subject, mail command:
GET nl-kr nl-kr_file_list
Web: http://ai.sunnyside.com/pub/nl-kr
Editors:
Al Whaley (al@ai.sunnyside.com) and
Chris Welty (weltyc@sigart.acm.org).
-----------------------------------------------------------------------
Date: Thu, 18 May 1995 12:52:21 -0700
To: nl-kr@ai.sunnyside.com (comp.ai.nlang-know-rep),
From: schlimme@eecs.wsu.edu (Jeffrey C. Schlimmer)
Subject: Program: ML12 Machine Learning, Jul 95, Tahoe City
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 Koza'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
Jeffrey C. Schlimmer, Asst. Prof., School of EE & CS, Washington State
University, Pullman, WA 99164-2752, (509) 335-2399, (509) 335-3818 FAX
http://www.eecs.wsu.edu/~schlimme/
End of NL-KR Digest
*******************
