Cargando…
Proceedings of the Fifth International Conference on Machine Learning : June 12-15, 1988, University of Michigan, Ann Arbor, Michigan /
Machine Learning Proceedings 1988.
| Clasificación: | Libro Electrónico |
|---|---|
| Autores Corporativos: | , |
| Otros Autores: | |
| Formato: | Electrónico Congresos, conferencias eBook |
| Idioma: | Inglés |
| Publicado: |
San Mateo, Calif. :
Morgan Kaufmann, Publishers,
[1988]
|
| Colección: | Proceedings - international conference on machine learning ;
5th |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Empirical learning : Using a generalization hierarchy to learn from examples / Randy G. Kerber ; Tuning rule-based systems to their environments / Hans Tallis ; On asking the right questions / Brent J. Krawchuk and Ian H. Witten ; concept simplification and prediction accuracy / Douglas H. Fisher and Jeffrey C. Schlimmer ; Learning graph models of shape / Jakub Segen ; Learning categorical decision criteria in biomedical domains / Kent A. Spackman ; Conceptual clumping of binary vectors with Occam's Razor / Jakub Segen ; AutoClass: a Bayesian classification system / Peter Cheeseman, James Kelly, Matthew Self, John Stutz, Will Taylor, and Don Freeman ; Incremental multiple concept learning using experiments / Klaus P. Gross ; Trading off simplicity and coverage in incremental concept learning / Wayne Iba, James Wogulis and Pat Langley ; Deferred commitment in UNIMEM: waiting to learn / Michael Lebowitz ; Experiments on the costs and benefits of windowing in ID3 / Jarryl Wirth and Jason Catlett ; Improved decision trees: a generalized version of ID3 / Jie Cheng, Usama M. Fayyad, Keki B. Irani and Zhaogang Qian ; ID5: in incremental ID3 / Paul E. Utgoff ; Using weighted networks to represent classification knowledge in noisy domains / Ming Tan and Larry Eshelman.
- Genetic learning : An empirical comparison of genetic and decision-tree classifiers / J.R. Quinlan ; Population size in classifier systems / George G. Robertson ; Representation and hidden bias: gray vs. binary coding for genetic algorithms / Richard A. Caruana and J. David Schaffer ; Classifier systems with hamming weights / Lawrence Davis and David K. Young ; Midgard: a genetic approach to adaptive load balancing for distributed systems / Adrian V. Sannier II and Erik D. Goodman
- Connectionist learning : Some interesting properties of a connectionist inductive learning system / Edward J. Wisniewski and James A. Anderson ; Competitive reinforcement learning / Kenton J. Lynne ; Connectionist learning of expert backgammon evaluations / G. Tesauro ; Building and using mental models in a sensory-motor domain: a connectionist approach / Bartlett W. Mel.
- Explanation-based learning : Reasoning about operationality for explanation-based learning / Haym Hirsh ; Boundaries of operationality / Michael S. Braverman and Stuart J. Russell ; On the tractability of learning from incomplete theories / Sridhar Mahadevan and Prasad Tadepalli ; Active explanation reduction: an approach to the multiple explanations problem / Shankar A. Rajamoney and Gerald F. DeJong ; Generalizing number and learning from multiple examples in explanation based learning / William W. Cohen ; Generalizing the order of operators in macro-operators / Raymond J. Mooney ; Using Experienced-based learning in game playing / Kenneth A. De Jong and Alan C. Schultz
- Integrated explanation-based and empirical learning : Integrated learning with incorrect and incomplete theories / Michael J. Pazzani ; An approach based on integrated learning to generating stories from stories / Claudio Carpiento ; A knowledge intensive approach to concept induction
- Case-based learning : Learning to program by examining and modifying cases / Robert S. Williams.
- Machine discovery : Theory discovery and the hypothesis language / Kevin T. Kelly ; Machine invention of first order predicates by inverting resolution / Stephen Muggleton and Wray Buntine ; The interdependencies of theory formation, revision, and experimentation / Brian Falkenhainer and Shankar Rajamoney ; A hill-climbing approach to machine discovery / Donald Rose and Pat Langley ; Reduction: a practical mechanism of searching for regularity in data / Yi-Hua Wu
- Formal models of concept learning : Extending the valiant learning model / Jonathan Amsterdam ; Learning systems of first-order rules / Nicolas Helft ; Two new frameworks for learning / B.K. Natarajan and P. Tadepalli ; Hypothesis filtering: a practical approach to reliable learning / Oren Etzioni
- Experimental results in machine learning : Diffy-S: learning robot operator schemata from examples / Carl M. Kadie ; Experimental results from an evaluation of algorithms that learn to control dynamic systems / Claude Sammut ; Utilizing experience for improving the tactical manager / Michael D. Erickson and Jan M. Zytkow
- Computational impact of learning and forgetting : Some chunks are expensive / Milind Tambe and Allen Newell
- The role of forgetting in learning / Shaul Markovitch and Paul D. Scott.