Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...
We put forth a framework for expressing security requirements from interactive protocols in the presence of arbitrary leakage. This allows capturing different levels of leakage to...
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-ran...
Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Pa...
Aiming at robust spoken dialogue interaction in motorcycle environment, we investigate various configurations for a speech front-end, which consists of speech pre-processing, spee...