Today many formalisms exist for specifying complex Markov chains. In contrast, formalisms for specifying rewards, enabling the analysis of long-run average performance properties,...
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies ...
Eduard Hoenkamp, Peter Bruza, Dawei Song, Qiang Hu...
In this paper, we develop a new "robust mixing" framework for reasoning about adversarially modified Markov Chains (AMMC). Let P be the transition matrix of an irreducib...
We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstructio...