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NIPS
2000
13 years 7 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, ...
TSP
2010
13 years 7 days ago
Markov chain monte carlo detectors for channels with intersymbol interference
In this paper, we propose novel low-complexity soft-in soft-out (SISO) equalizers using the Markov chain Monte Carlo (MCMC) technique. We develop a bitwise MCMC equalizer (b-MCMC) ...
Ronghui Peng, Rong-Rong Chen, Behrouz Farhang-Boro...
ICML
2008
IEEE
14 years 6 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
CVPR
2009
IEEE
14 years 3 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
CSDA
2011
13 years 17 days ago
Mapping electron density in the ionosphere: A principal component MCMC algorithm
The outer layers of the Earth’s atmosphere are known as the ionosphere, a plasma of free electrons and positively charged atomic ions. The electron density of the ionosphere var...
Eman Khorsheed, Merrilee Hurn, Christopher Jenniso...