Abstract. We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each o...
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Overgeneralization is a major issue in the identification of grammars for formal languages from positive data. Different formulations of generalization and specialization strate...