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Machine Learning, Volume 37, 1999

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Volume 37, Number 1, October 1999

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Sally A. Goldman, Stephen D. Scott:
A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns. 5-49
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Steven Hampson, Dennis F. Kibler:
Minimum Generalization Via Reflection: A Fast Linear Threshold Learner. 51-73
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Lawrence K. Saul, Michael I. Jordan:
Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones. 75-87
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Carlos Domingo, Nina Mishra, Leonard Pitt:
Efficient Read-Restricted Monotone CNF/DNF Dualization by Learning with Membership Queries. 89-110

Volume 37, Number 2, November 1999

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Leslie G. Valiant:
Projection Learning. 115-130
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Michael Schmitt:
On the Sample Complexity for Nonoverlapping Neural Networks. 131-141
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Leonardo Carbonara, Derek H. Sleeman:
Effective and Efficient Knowledge Base Refinement. 143-181
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Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul:
An Introduction to Variational Methods for Graphical Models. 183-233

Volume 37, Number 3, December 1999

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Jonathan Baxter, Nicolò Cesa-Bianchi:
Guest Editors' Introduction. 239-240
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Roni Khardon:
Learning Function-Free Horn Expressions. 241-275
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Yoav Freund, Robert E. Schapire:
Large Margin Classification Using the Perceptron Algorithm. 277-296
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Robert E. Schapire, Yoram Singer:
Improved Boosting Algorithms Using Confidence-rated Predictions. 297-336
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Philip M. Long:
The Complexity of Learning According to Two Models of a Drifting Environment. 337-354
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David A. McAllester:
Some PAC-Bayesian Theorems. 355-363

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