We consider the problem of computing information theoretic functions such as entropy on a data stream, using sublinear space. Our first result deals with a measure we call the &quo...
We survey a few concentration inequalities for submodular and fractionally subadditive functions of independent random variables, implied by the entropy method for self-bounding f...
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
Marques and Almeida [9] recently proposed a nonlinear data seperation technique based on the maximum entropy principle of Bell and Sejnowsky. The idea behind is a pattern repulsion...
Fabian J. Theis, Christoph Bauer, Carlos Garc&iacu...
—Given n discrete random variables = fX1;111; Xng, associated with any subset of f1; 2; 111; ng, there is a joint entropy H(X) where X = fXi:i 2 g. This can be viewed as a f...