Abstract. This work extends studies of Angluin, Lange and Zeugmann on the dependence of learning on the hypotheses space chosen for the class. In subsequent investigations, uniform...
We present Bayesian updating of an imprecise probability measure, represented by a class of precise multidimensional probability measures. Choice and analysis of our class are mot...
Abstract. This work extends studies of Angluin, Lange and Zeugmann on how learnability of a language class depends on the hypothesis space used by the learner. While previous studi...
Different formal learning models address different aspects of human learning. Below we compare Gold-style learning—interpreting learning as a limiting process in which the lear...
A general class of no-regret learning algorithms, called no-Φ-regret learning algorithms, is defined which spans the spectrum from no-external-regret learning to no-internal-reg...