ICML 1995

71 papers

A Bayesian Analysis of Algorithms for Learning Finite Functions James Cussens

A Case Study of Explanation-Based Control Gerald DeJong

A Comparative Evaluation of Voting and Meta-Learning on Partitioned Data Philip K. Chan, Salvatore J. Stolfo

A Comparison of Induction Algorithms for Selective and Non-Selective Bayesian Classifiers Moninder Singh, Gregory M. Provan

A Lexical Based Semantic Bias for Theory Revision Clifford Brunk, Michael J. Pazzani

A Quantitative Study of Hypothesis Selection Philip W. L. Fong

Active Exploration and Learning in Real-Valued Spaces Using Multi-Armed Bandit Allocation Indices Marcos Salganicoff, Lyle H. Ungar

An Inductive Learning Approach to Prognostic Prediction W. Nick Street, Olvi L. Mangasarian, William H. Wolberg

Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem Luca Maria Gambardella, Marco Dorigo

Automatic Parameter Selection by Minimizing Estimated Error Ron Kohavi, George H. John

Automatic Selection of Split Criterion During Tree Growing Based on Node Location Carla E. Brodley

Automatic Speaker Recognition: An Application of Machine Learning Brett Squires, Claude Sammut

Bounds on the Classification Error of the Nearest Neighbor Rule John A. Drakopoulos

Case-Based Acquisition of Place Knowledge Pat Langley, Karl Pfleger

Committee-Based Sampling for Training Probabilistic Classifiers Ido Dagan, Sean P. Engelson

Comparing Several Linear-Threshold Learning Algorithms on Tasks Involving Superfluous Attributes Nick Littlestone

Compression-Based Discretization of Continuous Attributes Bernhard Pfahringer

Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability Jürgen Schmidhuber

Distilling Reliable Information from Unreliable Theories Sean P. Engelson, Moshe Koppel

Efficient Algorithms for Finding Multi-Way Splits for Decision Trees Truxton Fulton, Simon Kasif, Steven Salzberg

Efficient Learning from Delayed Rewards Through Symbiotic Evolution David E. Moriarty, Risto Miikkulainen

Efficient Learning with Virtual Threshold Gates Wolfgang Maass, Manfred K. Warmuth

Efficient Memory-Based Dynamic Programming Jing Peng

Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain Avrim Blum

Error-Correcting Output Coding Corrects Bias and Variance Eun Bae Kong, Thomas G. Dietterich

Explanation-Based Learning and Reinforcement Learning: A Unified View Thomas G. Dietterich, Nicholas S. Flann

Fast and Efficient Reinforcement Learning with Truncated Temporal Differences Pawel Cichosz, Jan J. Mulawka

Fast Effective Rule Induction William W. Cohen

For Every Generalization Action, Is There Really an Equal and Opposite Reaction? R. Bharat Rao, Diana F. Gordon, William M. Spears

Free to Choose: Investigating the Sample Complexity of Active Learning of Real Valued Functions Partha Niyogi

Hill Climbing Beats Genetic Search on a Boolean Circuit Synthesis Problem of Koza's Kevin J. Lang

Horizonal Generalization David H. Wolpert

Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves David J. Lubinsky

Inductive Learning of Reactive Action Models Scott Benson

Inferring Reduced Ordered Decision Graphs of Minimum Description Length Arlindo L. Oliveira, Alberto L. Sangiovanni-Vincentelli

Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State R. Andrew McCallum

K*: An Instance-Based Learner Using and Entropic Distance Measure John G. Cleary, Leonard E. Trigg

Learning by Observation and Practice: An Incremental Approach for Planning Operator Acquisition Xuemei Wang

Learning Collection Fusion Strategies for Information Retrieval Geoffrey G. Towell, Ellen M. Voorhees, Narendra Kumar Gupta, Ben Johnson-Laird

Learning for Automotive Collision Avoidance and Autonomous Control Dean Pomerleau

Learning Hierarchies from Ambiguous Natural Language Data Takefumi Yamazaki, Michael J. Pazzani, Christopher J. Merz

Learning Policies for Partially Observable Environments: Scaling up Michael L. Littman, Anthony R. Cassandra, Leslie Pack Kaelbling

Learning Proof Heuristics by Adaptive Parameters Matthias Fuchs

Learning Prototypical Concept Descriptions Piew Datta, Dennis F. Kibler

Learning to Make Rent-to-Buy Decisions with Systems Applications P. Krishnan, Philip M. Long, Jeffrey Scott Vitter

Learning with Bayesian Networks (Abstract) David Heckerman

Learning with Rare Cases and Small Disjuncts Gary M. Weiss

Lessons from Theory Revision Applied to Constructive Induction Steven K. Donoho, Larry A. Rendell

Machine Learning and Information Retrieval (Abstract) W. Bruce Croft

MDL and Categorical Theories (Continued) J. Ross Quinlan

NewsWeeder: Learning to Filter Netnews Ken Lang

On Handling Tree-Structured Attributed in Decision Tree Learning Hussein Almuallim, Yasuhiro Akiba, Shigeo Kaneda

On Learning Decision Committees Richard Nock, Olivier Gascuel

On Pruning and Averaging Decision Trees Jonathan J. Oliver, David J. Hand

On-Line Learning of Binary Lexical Relations Using Two-Dimensional Weighted Majority Algorithms Naoki Abe, Hang Li, Atsuyoshi Nakamura

Protein Folding: Symbolic Refinement Competes with Neural Networks Susan Craw, Paul Hutton

Q-Learning for Bandit Problems Michael O. Duff

Reinforcement Learning by Stochastic Hill Climbing on Discounted Reward Hajime Kimura, Masayuki Yamamura, Shigenobu Kobayashi

Removing the Genetics from the Standard Genetic Algorithm Shumeet Baluja, Rich Caruana

Residual Algorithms: Reinforcement Learning with Function Approximation Leemon C. Baird Iii

Retrofitting Decision Tree Classifiers Using Kernel Density Estimation Padhraic Smyth, Alexander G. Gray, Usama M. Fayyad

Stable Function Approximation in Dynamic Programming Geoffrey J. Gordon

Supervised and Unsupervised Discretization of Continuous Features James Dougherty, Ron Kohavi, Mehran Sahami

Symbiosis in Multimodal Concept Learning Jukka Hekanaho

TD Models: Modeling the World at a Mixture of Time Scales Richard S. Sutton

Text Categorization and Relational Learning William W. Cohen

The Challenge of Revising an Impure Theory Russell Greiner

Theory and Applications of Agnostic PAC-Learning with Small Decision Trees Peter Auer, Robert C. Holte, Wolfgang Maass

Tracking the Best Expert Mark Herbster, Manfred K. Warmuth

Using Multidimensional Projection to Find Relations Eduardo Pérez, Larry A. Rendell

Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network Justine Blackmore, Risto Miikkulainen