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ICML
2008
IEEE
14 years 8 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
CAV
2009
Springer
187views Hardware» more  CAV 2009»
14 years 8 months ago
A Markov Chain Monte Carlo Sampler for Mixed Boolean/Integer Constraints
We describe a Markov chain Monte Carlo (MCMC)-based algorithm for sampling solutions to mixed Boolean/integer constraint problems. The focus of this work differs in two points from...
Nathan Kitchen, Andreas Kuehlmann
ICC
2009
IEEE
143views Communications» more  ICC 2009»
14 years 2 months 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...
NIPS
2000
13 years 8 months ago
Feature Correspondence: A Markov Chain Monte Carlo Approach
When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume tha...
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, ...
PRL
2006
163views more  PRL 2006»
13 years 7 months ago
3D target recognition using cooperative feature map binding under Markov Chain Monte Carlo
A robust and effective feature map integration method is presented for infrared (IR) target recognition. Noise in an IR image makes a target recognition system unstable in pose es...
Sungho Kim, In-So Kweon