This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
This paper focuses on confidence scores for use in acoustic model adaptation. Frame-based confidence estimates are used in linear transform (CMLLR and MLLR) and MAP adaptation. ...
In this paper, we cast discriminative training problems into standard linear programming (LP) optimization. Besides being convex and having globally optimal solution(s), LP progra...
We consider the problem of image comparison in order to match smooth surfaces under varying illumination. In a smooth surface nearby surface normals are highly correlated. We model...
Margarita Osadchy, Michael Lindenbaum, David W. Ja...