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» Speeeding Up Markov Chain Monte Carlo Algorithms
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CISS
2008
IEEE
14 years 1 days 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
JMLR
2010
139views more  JMLR 2010»
13 years 10 days ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
ICRA
2005
IEEE
149views Robotics» more  ICRA 2005»
13 years 11 months ago
A Markov Chain Monte Carlo Approach to Closing the Loop in SLAM
— The problem of simultaneous localization and mapping has received much attention over the last years. Especially large scale environments, where the robot trajectory loops back...
Michael Kaess, Frank Dellaert
ICC
2009
IEEE
143views Communications» more  ICC 2009»
14 years 9 days ago
Low Complexity Markov Chain Monte Carlo Detector for Channels with Intersymbol Interference
— In this paper, we propose a novel low complexity soft-in soft-out (SISO) equalizer using the Markov chain Monte Carlo (MCMC) technique. Direct application of MCMC to SISO equal...
Ronghui Peng, Rong-Rong Chen, Behrouz Farhang-Boro...
TCOM
2010
138views more  TCOM 2010»
13 years 3 months ago
Approaching MIMO capacity using bitwise Markov Chain Monte Carlo detection
—This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multipleinput and multiple-output (MIMO) channels. The proposed MCMC detector (Log...
Rong-Rong Chen, Ronghui Peng, Alexei Ashikhmin, Be...