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Machine learning : proceedings of the tenth international conference, University of Massachusetts, Amherst, June 27-29, 1993 /
Machine Learning Proceedings 1993.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | |
| Formato: | Electrónico Congresos, conferencias eBook |
| Idioma: | Inglés |
| Publicado: |
San Mateo, Calif. :
Morgan Kaufmann Pub.,
�1993.
|
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- The Evolution of Genetic Algorithms: Towards Massive Parallelism / Shumeet Baluja
- ELENA: A Bottom-Up Learning Method / Pierre Brezellec and Henry Soldano
- Addressing the Selective Superiority Problem: Automatic Algorithm/Model Class Selection / Carla E. Brodley
- Using Decision Trees to Improve Case-Based Learning / Claire Cardie
- GALOIS: An order-theoretic approach to conceptual clustering / Claudio Carpineto and Giovanni Romano
- Multitask Learning: A Knowledge-Based Source of Inductive Bias / Richard A. Caruana
- Using Qualitative Models to Guide Inductive Learning / Peter Clark and Stan Matwin
- Automating Path Analysis for Building Causal Models from Data / Paul R. Cohen, Adam Carlson, Lisa Ballesteros and Robert St. Amant
- Constructing Hidden Variables in Bayesian Networks via Conceptual Clustering / Dennis Connolly
- Learning Symbolic Rules Using Artificial Neural Networks / Mark W. Craven and Jude W. Shavlik.
- Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network / Andrea Pohoreckyj Danyluk and Foster John Provost
- Concept Sharing: A Means to Improve Multi-Concept Learning / Piew Datta and Dennis Kibler
- Discovering Dynamics / Saso Dzeroski and Ljupco Todorovski
- Synthesis of Abstraction Hierarchies for Constraint Satisfaction by Clustering Approximately Equivalent Objects / Thomas Ellman
- SKICAT: A Machine Learning System for Automated Cataloging of Large Scale Sky Surveys / Usama M. Fayyad, Nicholas Weir and S. Djorgovski
- Learning From Entailment: An Application to Propositional Horn Sentences / Michael Frazier and Leonard Pitt
- Efficient Domain-Independent Experimentation / Yolanda Gil
- Learning Search Control Knowledge for Deep Space Network Scheduling / Jonathan Gratch, Steve Chien and Gerald DeJong
- Learning procedures from interactive natural language instructions / Scott B. Huffman and John E. Laird.
- Generalization under Implication by Recursive Anti-unification / Peter Idestam-Almquist
- Supervised learning and divide-and-conquer: A statistical approach / Michael I. Jordan and Robert A. Jacobs
- Hierarchical Learning in Stochastic Domains: Preliminary Results / Leslie Pack Kaelbling
- Constraining Learning with Search Control / Jihie Kim and Paul S. Rosenbloom
- Sealing Up Reinforcement Learning for Robot Control / Long-Ji Lin
- Overcoming Incomplete Perception with Utile Distinction Memory / R. Andrew McCallum
- Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches / Tom M. Mitchell and Sebastian B. Thrun
- Combinatorial optimization in inductive concept learning / Dunja Mladenic
- Decision Theoretic Subsampling for Induction on Large Databases / Ron Musick, Jason Catlett and Stuart Russell
- Learning DNF Via Probabilistic Evidence Combination / Steven W. Norton and Haym Hirsh.
- Explaining and Generalizing Diagnostic Decisions / Paul O'Rorke, Yousri El Fattah and Margaret Elliott
- Combining Instance-Based and Model-Based Learning / J.R. Quinlan
- Data Mining of Subjective Agricultural Data / R. Bharat Rao, Thomas B. Voigt and Thomas W. Fermanian
- Lookahead Feature Construction for Learning Hard Concepts / Harish Ragavan and Larry Rendell
- Adaptive NeuroControl: How Black Box and Simple can it be / Jean Michel Renders, Hugues Bersini and Marco Saerens
- An SE-tree based Characterization of the Induction Problem / Ron Rymon
- Density-Adaptive Learning and Forgetting / Marcos Salganicoff
- Efficiently Inducing Determinations: A Complete and Systematic Search Algorithm that Uses Optimal Pruning / Jeffrey C. Schlimmer
- Compiling Bayesian Networks into Neural Networks / Eddie Schwalb
- A Reinforcement Learning Method for Maximizing Undiscounted Rewards / Anton Schwartz
- ATM Scheduling with Queuing Delay Predictions / Daniel B. Schwartz.
- Online Learning with Random Representations / Richard S. Sutton and Steven D. Whitehead
- Learning from Queries and Examples with Tree-structured Bias / Prasad Tadepalli
- Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents / Ming Tan
- Better Learners Use Analogical Problem Solving Sparingly / Kurt Van Lehn and Randolph M. Jones.