10. ICML 1993:
Amherst,
MA,
USA
Machine Learning,
Proceedings of the Tenth International Conference,
University of Massachusetts,
Amherst,
MA,
USA,
June 27-29,
1993. Morgan Kaufmann Prublishers,
ISBN 1-55860-307-7
- Shumeet Baluja:
The Evolution of Gennetic Algorithms: Towards Massive Parallelism.
1-8 BibTeX
- Pierre Brézellec, Henry Soldano:
ÉLÉNA: A Bottom-Up Learning Method.
9-16 BibTeX
- Carla E. Brodley:
Automatic Algorith/Model Class Selection.
17-24 BibTeX
- Claire Cardie:
Using Decision Trees to Improve Case-Based Learning.
25-32 BibTeX
- Claudio Carpineto, Giovanni Romano:
GALOIS: An Order-Theoretic Approach to Conceptual Clustering.
33-40 BibTeX
- Rich Caruana:
Multitask Learning: A Knowledge-Based Source of Inductive Bias.
41-48 BibTeX
- Peter Clark, Stan Matwin:
Using Qualitative Models to Guide Inductive Learning.
49-56 BibTeX
- Paul R. Cohen, Adam Carlson, Lisa Ballesteros, Adam St. Amant:
Automating Path Analysis for Building Causal Models from Data.
57-64 BibTeX
- Dennis Connolly:
Constructing Hidden Variables in Bayesian Networks via Conceptual Clustering.
65-72 BibTeX
- Mark Craven, Jude W. Shavlik:
Learning Symbolic Rules Using Artificial Neural Networks.
73-80 BibTeX
- Andrea Pohoreckyj Danyluk, Foster J. Provost:
Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network.
81-88 BibTeX
- Piew Datta, Dennis F. Kibler:
Concept Sharing: A Means to Improve Multi-Concept Learning.
89-96 BibTeX
- Saso Dzeroski, Ljupco Todorovski:
Discovering Dynamics.
97-103 BibTeX
- Thomas Ellman:
Synthesis of Abstraction Hierarchies for Constraint Satisfaction by Clustering Approximately Equivalent Objects.
104-111 BibTeX
- Usama M. Fayyad, Nicholas Weir, S. George Djorgovski:
SKICAT: A Machine Learning System for Automated Cataloging of Large Scale Sky Surveys.
112-119 BibTeX
- Michael Frazier, Leonard Pitt:
Learning From Entailment: An Application to Propositional Horn Sentences.
120-127 BibTeX
- Yolanda Gil:
Efficient Domain-Independent Experimentation.
128-134 BibTeX
- Jonathan Gratch, Steve A. Chien, Gerald DeJong:
Learning Search Control Knowledge for Deep Space Network Scheduling.
135-142 BibTeX
- Scott B. Huffman, John E. Laird:
Learning Procedures from Interactive Natural Language Instructions.
143-150 BibTeX
- Peter Idestam-Almquist:
Generalization under Implication by Recursive Anti-unification.
151-158 BibTeX
- Michael I. Jordan, Robert A. Jacobs:
Supervised Learning and Divide-and-Conquer: A Statistical Approach.
159-166 BibTeX
- Leslie Pack Kaelbling:
Hierarchical Learning in Stochastic Domains: Preliminary Results.
167-173 BibTeX
- Jihie Kim, Paul S. Rosenbloom:
Constraining Learning with Search Control.
174-181 BibTeX
- Long Ji Lin:
Scaling Up Reinforcement Learning for Robot Control.
182-189 BibTeX
- Andrew McCallum:
Overcoming Incomplete Perception with Util Distinction Memory.
190-196 BibTeX
- Tom M. Mitchell, Sebastian Thrun:
Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches.
197-204 BibTeX
- Dunja Mladenic:
Combinatorial Optimization in Inductive Concept Learning.
205-211 BibTeX
- Ron Musick, Jason Catlett, Stuart J. Russell:
Decision Theoretic Subsampling for Induction on Large Databases.
212-219 BibTeX
- Steven W. Norton, Haym Hirsh:
Learning DNF Via Probabilistic Evidence Combination.
220-227 BibTeX
- Paul O'Rorke, Yousri El Fattah, Margaret Elliott:
Explaining and Generalizing Diagnostic Decisions.
228-235 BibTeX
- J. Ross Quinlan:
Combining Instance-Based and Model-Based Learning.
236-243 BibTeX
- R. Bharat Rao, Thomas B. Voigt, Thomas W. Fermanian:
Data Mining of Subjective Agricultural Data.
244-251 BibTeX
- Harish Ragavan, Larry A. Rendell:
Lookahead Feature Construction for Learning Hard Concepts.
252-259 BibTeX
- Jean-Michel Renders, Hugues Bersini, Marco Saerens:
Adaptive NeuroControl: How Black Box and Simple can it be.
260-267 BibTeX
- Ron Rymon:
An SE-tree based Characterization of the Induction Problem.
268-275 BibTeX
- Marcos Salganicoff:
Density-Adaptive Learning and Forgetting.
276-283 BibTeX
- Jeffrey C. Schlimmer:
Efficiently Inducing Determinations: A Complete and Systematic Search Algorithm that Uses Optimal Pruning.
284-290 BibTeX
- Eddie Schwalb:
Compiling Bayesian Networks into Neural Networks.
291-297 BibTeX
- Anton Schwartz:
A Reinforcement Learning Method for Maximizing Undiscounted Rewards.
298-305 BibTeX
- Daniel B. Schwartz:
ATM SCheduling with Queuing Dely Predictions.
306-313 BibTeX
- Richard S. Sutton, Steven D. Whitehead:
Online Learning with Random Representations.
314-321 BibTeX
- Prasad Tadepalli:
Learning from Queries and Examples with Tree-structured Bias.
322-329 BibTeX
- Ming Tan:
Multi-Agent Reinforcement Learning: Independent versus Cooperative Agents.
330-337 BibTeX
- Kurt VanLehn, Randolph M. Jones:
Better Learners Use Analogical Problem Solving Sparingly.
338-345 BibTeX
Copyright © Sat May 16 23:20:39 2009
by Michael Ley (ley@uni-trier.de)
