In a previous paper we proposed Web-based language models relying on the possibility theory. These models explicitly represent the possibility of word sequences. In this paper we ...
Stanislas Oger, Vladimir Popescu, Georges Linar&eg...
A new mapping algorithm for speech recognition relates the features of simultaneous recordings of clean and noisy speech. The model is a piecewise nonfinear transformation appfied...
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Abstract. This paper is concerned with one of the basic problems in abstract interpretation, namely, for a given abstraction and a given set of concrete transformers (that express ...
Tal Lev-Ami, Mooly Sagiv, Neil Immerman, Thomas W....