We present a novel approach to constraintbased causal discovery, that takes the form of straightforward logical inference, applied to a list of simple, logical statements about ca...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
We propose a novel sequential decision approach to modeling ordinal ratings in collaborative filtering problems. The rating process is assumed to start from the lowest level, eva...
Abstract. This paper investigates a new extension of the Probabilistic Latent Semantic Analysis (PLSA) model [6] for text classification where the training set is partially labeled...
Abstract. We propose a convex optimization approach to solving the nonparametric regression estimation problem when the underlying regression function is Lipschitz continuous. This...
Dimitris Bertsimas, David Gamarnik, John N. Tsitsi...