We consider two basic computational problems regarding discrete probability distributions: (1) approximating the statistical difference (aka variation distance) between two given d...
We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this probl...
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
When comparing discrete probability distributions, natural measures of similarity are not p distances but rather are informationdivergences such as Kullback-Leibler and Hellinger. ...
Abstract. Probabilistic timed automata are an extension of timed automata with discrete probability distributions. In previous work, a probabilistic notion of time divergence for p...
Abstract-- This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variable...