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TCOM
2010
138views more  TCOM 2010»
14 years 10 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...
JMLR
2010
139views more  JMLR 2010»
14 years 7 months 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...
JSAC
2008
102views more  JSAC 2008»
15 years 8 days ago
Convergence of Markov-Chain Monte-Carlo Approaches to Multiuser and MIMO Detection
Markov-chain Monte
Soren J. Henriksen, Brett Ninness, Steven R. Welle...
JSC
2006
106views more  JSC 2006»
15 years 7 days ago
Markov bases for noncommutative Fourier analysis of ranked data
To calibrate Fourier analysis of S5 ranking data by Markov chain Monte Carlo techniques, a set of moves (Markov basis) is needed. We calculate this basis, and use it to provide a ...
Persi Diaconis, Nicholas Eriksson
DATE
2010
IEEE
171views Hardware» more  DATE 2010»
15 years 5 months ago
Statistical static timing analysis using Markov chain Monte Carlo
—We present a new technique for statistical static timing analysis (SSTA) based on Markov chain Monte Carlo (MCMC), that allows fast and accurate estimation of the right-hand tai...
Yashodhan Kanoria, Subhasish Mitra, Andrea Montana...