The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
We evaluate a new hybrid language processing approach designed for interactive applications that maintain an interaction with users over multiple turns. Specifically, we describe ...
The problem of group ranking, a.k.a. rank aggregation, has been studied in contexts varying from sports, to multi-criteria decision making, to machine learning, to ranking web pag...
Output coding is a general framework for solving multiclass categorization problems. Previous research on output codes has focused on building multiclass machines given predefine...
When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of complexity/current loss renders the analys...