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Machine Learning: From Theory to Applications

Keyphrases

Publications

1993

Michael J. Kearns, Leslie G. Valiant
Cryptographic Limitations on Learning Boolean Formulae and Finite Automata. Machine Learning: From Theory to Applications (1993)
Regine Meunier, Ruxandra Scheiterer, Angelika Hecht
Learning of Rules for Fault Diagnosis in Power Supply Networks. Machine Learning: From Theory to Applications (1993)
Avrim Blum, Ronald L. Rivest
Training a 3-Node Neural Network is NP-Complete. Machine Learning: From Theory to Applications (1993)
R. Chou, Peiya Liu, James R. Vallino, M. Y. Chiu
Behavior-Based Learning to Control IR Oven Heating: Preliminary Investigations. Machine Learning: From Theory to Applications (1993)
Robert W. Schwanke, Michael A. Platoff
Cross References are Features. Machine Learning: From Theory to Applications (1993)
Stephen Jose Hanson, Werner Remmele, Ronald L. Rivest
Strategic Directions in Machine Learning. Machine Learning: From Theory to Applications (1993)
Stephen Jose Hanson
Introduction. Machine Learning: From Theory to Applications (1993)
Neeraj Bhatnagar
Adaptive Search by Learning from Incomplete Explanations of Failures. Machine Learning: From Theory to Applications (1993)
Kai Zercher
L-ATMS: A Tight Integration of EBL and the ATMS. Machine Learning: From Theory to Applications (1993)
Raymond L. Watrous
Phoneme Discrimination Using Connectionist Networks. Machine Learning: From Theory to Applications (1993)
Ronald L. Rivest
Introduction. Machine Learning: From Theory to Applications (1993)
Werner Remmele
Introduction. Machine Learning: From Theory to Applications (1993)
Richard H. Lathrop, Teresa A. Webster, Temple F. Smith, Patrick H. Winston
Massively Parallel Symbolic Induction of Protein Structure/Function Relationships. Machine Learning: From Theory to Applications (1993)
Gary L. Drescher
The Schema Mechanism. Machine Learning: From Theory to Applications (1993)
Ronald L. Rivest, Robert E. Schapire
Inference of Finite Automata Using Homing Sequences. Machine Learning: From Theory to Applications (1993)
Thomas Petsche, Bradley W. Dickinson
Trellis Codes, Receptive Fields, and Fault Tolerant, Self-Repairing Neural Networks. Machine Learning: From Theory to Applications (1993)
Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Machine Learning: From Theory to Applications (1993)

volume 661, 1993

Machine Learning: From Theory to Applications - Cooperative Research at Siemens and MIT Machine Learning: From Theory to Applications 661 (1993)