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TCOM
2010
138views more  TCOM 2010»
13 years 5 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»
13 years 2 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»
13 years 7 months 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»
13 years 7 months 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»
14 years 19 days 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...