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

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 Jaakkola, Lawrence K. Saul: An Introduction to Variational Methods for Graphical Models. 183-233

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