We investigate under what conditions clustering by learning a mixture of spherical Gaussians is (a) computationally tractable; and (b) statistically possible. We show that using p...
Nathan Srebro, Gregory Shakhnarovich, Sam T. Rowei...
This paper presents a learning theoretical analysis of correlation clustering (Bansal et al., 2002). In particular, we give bounds on the error with which correlation clustering r...
This paper describes the Bar-Ilan system participating in the Recognising Textual Entailment Challenge. The paper proposes first a general probabilistic setting that formalizes th...
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
We propose a method to recognize the `social attitude' of users towards an Embodied Conversational Agent (ECA) from a combination of linguistic and prosodic features. After de...
Fiorella de Rosis, Anton Batliner, Nicole Novielli...