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ORCID5th ML 1988: Ann Arbor, Michigan, USA
- John E. Laird:
Machine Learning, Proceedings of the Fifth International Conference on Machine Learning, Ann Arbor, Michigan, USA, June 12-14, 1988. Morgan Kaufmann 1988, ISBN 0-934613-64-8
Empirical Learning
- Randy Kerber:
Using a Generalization Hierarchy to Learn from Examples. ML 1988: 1-7 - Hans Tallis:
Tuning Rule-Based Systems to Their Environments. ML 1988: 8-14 - Brent J. Krawchuk, Ian H. Witten:
On Asking the Right Questions. ML 1988: 15-21 - Douglas H. Fisher, Jeffrey C. Schlimmer:
Concept Simplification and Prediction Accuracy. ML 1988: 22-28 - Jakub Segen:
Learning Graph Models of Shape. ML 1988: 29-35 - Kent A. Spackman:
Learning Categorical Decision Criteria in Biomedical Domains. ML 1988: 36-46 - Jakub Segen:
Conceptual Clumping of Binary Vectors with Occam's Razor. ML 1988: 47-53 - Peter C. Cheeseman, James Kelly, Matthew Self, John C. Stutz, Will Taylor, Don Freeman:
AutoClass: A Bayesian Classification System. ML 1988: 54-64 - Klaus P. Gross:
Incremental Multiple Concept Learning Using Experiments. ML 1988: 65-72 - Wayne Iba, James Wogulis, Pat Langley:
Trading Off Simplicity and Coverage in Incremental concept Learning. ML 1988: 73-79 - Michael Lebowitz:
Deferred Commitment in UNIMEM: Waiting to Learn. ML 1988: 80-86 - Jarryl Wirth, Jason Catlett:
Experiments on the Costs and Benefits of Windowing in ID3. ML 1988: 87-99 - Jie Cheng, Usama M. Fayyad, Keki B. Irani, Zhaogang Qian:
Improved Decision Trees: A Generalized Version of ID3. ML 1988: 100-106 - Paul E. Utgoff:
ID5: An Incremental ID3. ML 1988: 107-120 - Ming Tan, Larry J. Eshelman:
Using Weighted Networks to Represent Classification Knowledge in Noisy Domains. ML 1988: 121-134
Genetic Learning
- J. Ross Quinlan:
An Empirical Comparison of Genetic and Decision-Tree Classifiers. ML 1988: 135-141 - George G. Robertson:
Population Size in classifier Systems. ML 1988: 142-152 - Rich Caruana, J. David Schaffer:
Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms. ML 1988: 153-161 - Lawrence Davis, David K. Young:
Classifier Systems with Hamming Weights. ML 1988: 162-173 - Adrian V. Sannier II, Erik D. Goodman:
Midgard: A Genetic Approach to Adaptive Load Balancing for Distributed Systems. ML 1988: 174-180
Connectionist Learning
- Edward J. Wisniewski, James A. Anderson:
Some Interesting Properties of a Connectionist Inductive Learning System. ML 1988: 181-187 - Kenton J. Lynne:
Competitive Reinforcement Learning. ML 1988: 188-199 - Gerald Tesauro:
Connectionist Learning of Expert Backgammon Evaluations. ML 1988: 200-206 - Bartlett W. Mel:
Building and Using Mental Models in a Sensory-Motor Domain. ML 1988: 207-213
Explanation-Based Learning
- Haym Hirsh:
Reasoning about Operationality for Explanation-Based Learning. ML 1988: 214-220 - Michael S. Braverman, Stuart J. Russell:
Boundaries of Operationality. ML 1988: 221-234 - Sridhar Mahadevan, Prasad Tadepalli:
On the Tractability of Learning from Incomplete Theories. ML 1988: 235-241 - Shankar A. Rajamoney, Gerald DeJong:
Active Explanation Reduction: An Approach to the Multiple Explanations Problem. ML 1988: 242-255 - William W. Cohen:
Generalizing Number and Learning from Multiple Examples in Explanation Based Learning. ML 1988: 256-269 - Raymond J. Mooney:
Generalizing the Order of Operators in Macro-Operators. ML 1988: 270-283 - Kenneth A. De Jong, Alan C. Schultz:
Using Experience-Based Learning in Game Playing. ML 1988: 284-290
Integrated Explanation-Based and Empirical Learning
- Michael J. Pazzani:
Integrated Learning with Incorrect and Incomplete Theories. ML 1988: 291-297 - Claudio Carpineto:
An Approach Based on Integrated Learning to Generating Stories. ML 1988: 298-304 - Francesco Bergadano, Attilio Giordana:
A Knowledge Intensive Approach to Concept Induction. ML 1988: 305-317
Case-Based Learning
- Robert S. Williams:
Learning to Program by Examining and Modifying Cases. ML 1988: 318-324
Machine Discovery
- Kevin T. Kelly:
Theory Discovery and the Hypothesis Language. ML 1988: 325-338 - Stephen H. Muggleton, Wray L. Buntine:
Machine Invention of First Order Predicates by Inverting Resolution. ML 1988: 339-352 - Brian Falkenhainer, Shankar A. Rajamoney:
The Interdependencies of Theory Formation, Revision, and Experimentation. ML 1988: 353-366 - Donald Rose, Pat Langley:
A Hill-Climbing Approach to Machine Discovery. ML 1988: 367-373 - Yi-Hua Wu:
Reduction: A Practical Mechanism of Searching for Regularity in Data. ML 1988: 374-380
Formal Models of Concept Learning
- Jonathan Amsterdam:
Extending the Valiant Learning Model. ML 1988: 381-394 - Nicolas Helft:
Learning Systems of First-Order Rules. ML 1988: 395-401 - Balas K. Natarajan, Prasad Tadepalli:
Two New Frameworks for Learning. ML 1988: 402-415 - Oren Etzioni:
Hypothesis Filtering: A Practical Approach to Reliable Learning. ML 1988: 416-429
Experimental Results in Machine Learning
- Carl Myers Kadie:
Diffy-S: Learning Robot Operator Schemata from Examples. ML 1988: 430-436 - Claude Sammut:
Experimental Results from an Evaluation of Algorithms that Learn to Control Dynamic Systems. ML 1988: 437-443 - Michael D. Erickson, Jan M. Zytkow:
Utilizing Experience for Improving the Tactical Manager. ML 1988: 444-450
Computational Impact of Learning and Forgetting
- Milind Tambe, Allen Newell:
Some Chunks Are Expensive. ML 1988: 451-458 - Shaul Markovitch, Paul D. Scott:
The Role of Forgetting in Learning. ML 1988: 459-465
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