Learning with Probabilistic Representations
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Bayesian Network Classifiers
The Sample Complexity of Learning Fixed-Structure Bayesian Networks
Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables
Adaptive Probabilistic Networks with Hidden Variables
Factorial Hidden Markov Models
Predicting Protein Secondary Structure Using Stochastic Tree Grammars
Decision Tree Induction Based on Efficient Tree Restructuring
Online Learning versus Offline Learning
Coping with Uncertainty in Map Learning