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ORCIDMachine Learning, Volume 5
Volume 5, 1990
- Thomas G. Dietterich:
Exploratory Research in Machine Learning. 5-9 - Derek H. Sleeman:
Extending Domain Theories: Two Case Studies in Student Modeling. 11-37 - Jude W. Shavlik:
Acquiring Recursive and Iterative Concepts with Explanation-Based Learning. 39-40 - Giulia Pagallo, David Haussler:
Boolean Feature Discovery in Empirical Learning. 71-99 - Haim Schweitzer:
A Necessary Condition for Learning from Positive Examples. 101-113 - Leonard Pitt:
Introduction: Special Issue on Computational Learning Theory. 117-120 - Dana Angluin:
Negative Results for Equivalence Queries. 121-150 - Hiroki Ishizaka:
Polynomial time Learnability of Simple Deterministic Languages. 151-164 - David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth:
Learning Nested Differences of Intersection-Closed Concept Classes. 165-196 - Robert E. Schapire:
The Strength of Weak Learnability. 197-227 - Pat Langley:
Advice to Machine Learning Authors. Mach. Learn. 5: 233-237 (1990) - J. Ross Quinlan:
Learning Logical Definitions from Relations. 239-266 - Larry A. Rendell, Howard Cho:
Empirical Learning as a Function of Concept Character. 267-298 - Milind Tambe, Allen Newell, Paul S. Rosenbloom:
The Problem of Expensive Chunks and its Solution by Restricting Expressiveness. 299-348 - John J. Grefenstette, Connie Loggia Ramsey, Alan C. Schultz:
Learning Sequential Decision Rules Using Simulation Models and Competition. 355-381 - Hayong Harry Zhou:
CSM: A Computational Model of Cumulative Learning. 383-406 - David E. Goldberg:
Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding. 407-425 - David J. Montana:
Empirical Learning Using Rule Threshold Optimization for Detection of Events in Synthetic Images. 427-450
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