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CISS
2008
IEEE
14 years 2 months ago
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
— 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...
Shirin Jalali, Tsachy Weissman
CORR
2008
Springer
127views Education» more  CORR 2008»
13 years 7 months ago
On the long time behavior of the TCP window size process
The TCP window size process appears in the modeling of the famous Transmission Control Protocol used for data transmission over the Internet. This continuous time Markov process t...
Djalil Chafaï, Florent Malrieu, Katy Paroux
ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
CORR
2008
Springer
121views Education» more  CORR 2008»
13 years 7 months ago
Rate-Distortion via Markov Chain Monte Carlo
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...
Shirin Jalali, Tsachy Weissman
ICRA
2007
IEEE
154views Robotics» more  ICRA 2007»
14 years 1 months ago
Oracular Partially Observable Markov Decision Processes: A Very Special Case
— We introduce the Oracular Partially Observable Markov Decision Process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an “oracle,” ...
Nicholas Armstrong-Crews, Manuela M. Veloso