Inductive process modeling
Joint feature re-extraction and classification using an iterative semi-supervised support vector machine algorithm
A k-norm pruning algorithm for decision tree classifiers based on error rate estimation
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Discovering significant patterns
Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move
Learning symmetric causal independence models
Learning (k,l)-contextual tree languages for information extraction from web pages
Learning the structure of dynamic Bayesian networks from time series and steady state measurements
On reoptimizing multi-class classifiers
Efficient approximate leave-one-out cross-validation for kernel logistic regression
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns