12. ICML 1995:
Tahoe City,
California,
USA
Armand Prieditis,
Stuart J. Russell (Eds.):
Machine Learning,
Proceedings of the Twelfth International Conference on Machine Learning,
Tahoe City,
California,
USA,
July 9-12,
1995. Morgan Kaufmann,
ISBN 1-55860-377-8
Contributed Papers
- Naoki Abe, Hang Li, Atsuyoshi Nakamura:
On-line Learning of Binary Lexical Relations Using Two-dimensional Weighted Majority Algorithms.
3-11 BibTeX
- Hussein Almuallim, Yasuhiro Akiba, Shigeo Kaneda:
On Handling Tree-Structured Attributed in Decision Tree Learning.
12-20 BibTeX
- Peter Auer, Robert C. Holte, Wolfgang Maass:
Theory and Applications of Agnostic PAC-Learning with Small Decision Trees.
21-29 BibTeX
- Leemon C. Baird III:
Residual Algorithms: Reinforcement Learning with Function Approximation.
30-37 BibTeX
- Shumeet Baluja, Rich Caruana:
Removing the Genetics from the Standard Genetic Algorithm.
38-46 BibTeX
- Scott Benson:
Inductive Learning of Reactive Action Models.
47-54 BibTeX
- Justine Blackmore, Risto Miikkulainen:
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network.
55-63 BibTeX
- Avrim Blum:
Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain.
64-72 BibTeX
- Carla E. Brodley:
Automatic Selection of Split Criterion during Tree Growing Based on Node Location.
73-80 BibTeX
- Clifford Brunk, Michael J. Pazzani:
A Lexical Based Semantic Bias for Theory Revision.
81-89 BibTeX
- Philip K. Chan, Salvatore J. Stolfo:
A Comparative Evaluation of Voting and Meta-learning on Partitioned Data.
90-98 BibTeX
- Pawel Cichosz, Jan J. Mulawka:
Fast and Efficient Reinforcement Learning with Truncated Temporal Differences.
99-107 BibTeX
- John G. Cleary, Leonard E. Trigg:
K*: An Instance-based Learner Using and Entropic Distance Measure.
108-114 BibTeX
- William W. Cohen:
Fast Effective Rule Induction.
115-123 BibTeX
- William W. Cohen:
Text Categorization and Relational Learning.
124-132 BibTeX
- Susan Craw, Paul Hutton:
Protein Folding: Symbolic Refinement Competes with Neural Networks.
133-141 BibTeX
- James Cussens:
A Bayesian Analysis of Algorithms for Learning Finite Functions.
142-149 BibTeX
- Ido Dagan, Sean P. Engelson:
Committee-Based Sampling For Training Probabilistic Classifiers.
150-157 BibTeX
- Piew Datta, Dennis F. Kibler:
Learning Prototypical Concept Descriptions.
158-166 BibTeX
- Gerald DeJong:
A Case Study of Explanation-Based Control.
167-175 BibTeX
- Thomas G. Dietterich, Nicholas S. Flann:
Explanation-Based Learning and Reinforcement Learning: A Unified View.
176-184 BibTeX
- Steven K. Donoho, Larry A. Rendell:
Lessons from Theory Revision Applied to Constructive Induction.
185-193 BibTeX
- James Dougherty, Ron Kohavi, Mehran Sahami:
Supervised and Unsupervised Discretization of Continuous Features.
194-202 BibTeX
- John A. Drakopoulos:
Bounds on the Classification Error of the Nearest Neighbor Rule.
203-208 BibTeX
- Michael O. Duff:
Q-Learning for Bandit Problems.
209-217 BibTeX
- Sean P. Engelson, Moshe Koppel:
Distilling Reliable Information From Unreliable Theories.
218-225 BibTeX
- Philip W. L. Fong:
A Quantitative Study of Hypothesis Selection.
226-234 BibTeX
- Matthias Fuchs:
Learning Proof Heuristics by Adaptive Parameters.
235-243 BibTeX
- Truxton Fulton, Simon Kasif, Steven Salzberg:
Efficient Algorithms for Finding Multi-way Splits for Decision Trees.
244-251 BibTeX
- Luca Maria Gambardella, Marco Dorigo:
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem.
252-260 BibTeX
- Geoffrey J. Gordon:
Stable Function Approximation in Dynamic Programming.
261-268 BibTeX
- Russell Greiner:
The Challenge of Revising an Impure Theory.
269-277 BibTeX
- Jukka Hekanaho:
Symbiosis in Multimodal Concept Learning.
278-285 BibTeX
- Mark Herbster, Manfred K. Warmuth:
Tracking the Best Expert.
286-294 BibTeX
- Hajime Kimura, Masayuki Yamamura, Shigenobu Kobayashi:
Reinforcement Learning by Stochastic Hill Climbing on Discounted Reward.
295-303 BibTeX
- Ron Kohavi, George H. John:
Autmatic Parameter Selection by Minimizing Estimated Error.
304-312 BibTeX
- Eun Bae Kong, Thomas G. Dietterich:
Error-Correcting Output Coding Corrects Bias and Variance.
313-321 BibTeX
- P. Krishnan, Philip M. Long, Jeffrey Scott Vitter:
Learning to Make Rent-to-Buy Decisions with Systems Applications.
233-330 BibTeX
- Ken Lang:
NewsWeeder: Learning to Filter Netnews.
331-339 BibTeX
- Kevin J. Lang:
Hill Climbing Beats Genetic Search on a Boolean Circuit Synthesis Problem of Koza's.
340-343 BibTeX
- Pat Langley, Karl Pfleger:
Case-Based Acquisition of Place Knowledge.
344-352 BibTeX
- Nick Littlestone:
Comparing Several Linear-threshold Learning Algorithms on Tasks Involving Superfluous Attributes.
353-361 BibTeX
- Michael L. Littman, Anthony R. Cassandra, Leslie Pack Kaelbling:
Learning Policies for Partially Observable Environments: Scaling Up.
362-370 BibTeX
- David J. Lubinsky:
Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves.
371-377 BibTeX
- Wolfgang Maass, Manfred K. Warmuth:
Efficient Learning with Virtual Threshold Gates.
378-386 BibTeX
- Andrew McCallum:
Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State.
387-395 BibTeX
- David E. Moriarty, Risto Miikkulainen:
Efficient Learning from Delayed Rewards through Symbiotic Evolution.
396-404 BibTeX
- Partha Niyogi:
Free to Choose: Investigating the Sample Complexity of Active Learning of Real Valued Functions.
405-412 BibTeX
- Richard Nock, Olivier Gascuel:
On Learning Decision Committees.
413-420 BibTeX
- Arlindo L. Oliveira, Alberto L. Sangiovanni-Vincentelli:
Inferring Reduced Ordered Decision Graphs of Minimum Description Length.
421-429 BibTeX
- Jonathan J. Oliver, David J. Hand:
On Pruning and Averaging Decision Trees.
430-437 BibTeX
- Jing Peng:
Efficient Memory-Based Dynamic Programming.
438-446 BibTeX
- Eduardo Pérez, Larry A. Rendell:
Using Multidimensional Projection to Find Relations.
447-455 BibTeX
- Bernhard Pfahringer:
Compression-Based Discretization of Continuous Attributes.
456-463 BibTeX
- J. Ross Quinlan:
MDL and Categorial Theories (Continued).
464-470 BibTeX
- R. Bharat Rao, Diana F. Gordon, William M. Spears:
For Every Generalization Action, Is There Really an Equal and Opposite Reaction?
471-479 BibTeX
- Marcos Salganicoff, Lyle H. Ungar:
Active Exploration and Learning in real-Valued Spaces using Multi-Armed Bandit Allocation Indices.
480-487 BibTeX
- Jürgen Schmidhuber:
Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability.
488-496 BibTeX
- Moninder Singh, Gregory M. Provan:
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers.
497-505 BibTeX
- Padhraic Smyth, Alexander Gray, Usama M. Fayyad:
Retrofitting Decision Tree Classifiers Using Kernel Density Estimation.
506-514 BibTeX
- Brett Squires, Claude Sammut:
Automatic Speaker Recognition: An Application of Machine Learning.
515-521 BibTeX
- W. Nick Street, Olvi L. Mangasarian, W. H. Wolberg:
An Inductive Learning Approach to Prognostic Prediction.
522-530 BibTeX
- Richard S. Sutton:
TD Models: Modeling the World at a Mixture of Time Scales.
531-539 BibTeX
- Geoffrey G. Towell, Ellen M. Voorhees, Narendra Kumar Gupta, Ben Johnson-Laird:
Learning Collection FUsion Strategies for Information Retrieval.
540-548 BibTeX
- Xuemei Wang:
Learning by Observation and Practice: An Incremental Approach for Planning Operator Acquisition.
549-557 BibTeX
- Gary M. Weiss:
Learning with Rare Cases and Small Disjuncts.
558-565 BibTeX
- David Wolpert:
Horizonal Generalization.
566-574 BibTeX
- Takefumi Yamazaki, Michael J. Pazzani, Christopher J. Merz:
Learning Hierarchies from Ambiguous Natural Language Data.
575-583 BibTeX
Invited Talks
Copyright © Sat May 16 23:20:39 2009
by Michael Ley (ley@uni-trier.de)
