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 present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
— Model reduction methods from diverse fields— including control, statistical mechanics and economics—aimed at systems that can be represented by Markov chains, are discusse...
Carolyn L. Beck, Sanjay Lall, Tzuchen Liang, Matth...
An information-theoretic model for steganography with passive adversaries is proposed. The adversary's task of distinguishing between an innocent cover message C and a modi e...
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...