In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
In this paper, we propose to model the blended search problem by assuming conditional dependencies among queries, VSEs and search results. The probability distributions of this mo...
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Recently, Multiple Background Models (M-BMs) [1, 2] have been shown to be useful in speaker verification, where the M-BMs are formed based on different Vocal Tract Lengths (VTLs)...