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Machine Learning, Volume 37, 1999
Volume 37, Number 1, October 1999
- Sally A. Goldman, Stephen D. Scott:
A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns. 5-49 - Steven Hampson, Dennis F. Kibler:
Minimum Generalization Via Reflection: A Fast Linear Threshold Learner. 51-73 - Lawrence K. Saul, Michael I. Jordan:
Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones. 75-87 - 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
- Leslie G. Valiant:
Projection Learning. 115-130 - Michael Schmitt:
On the Sample Complexity for Nonoverlapping Neural Networks. 131-141 - Leonardo Carbonara, Derek H. Sleeman:
Effective and Efficient Knowledge Base Refinement. 143-181 - 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
- Jonathan Baxter, Nicolò Cesa-Bianchi:
Guest Editors' Introduction. 239-240 - Roni Khardon:
Learning Function-Free Horn Expressions. 241-275 - Yoav Freund, Robert E. Schapire:
Large Margin Classification Using the Perceptron Algorithm. 277-296 - Robert E. Schapire, Yoram Singer:
Improved Boosting Algorithms Using Confidence-rated Predictions. 297-336 - Philip M. Long:
The Complexity of Learning According to Two Models of a Drifting Environment. 337-354 - David A. McAllester:
Some PAC-Bayesian Theorems. 355-363
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