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NIPS
2000
13 years 10 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, ...
TASLP
2008
124views more  TASLP 2008»
13 years 8 months ago
Sparse Linear Regression With Structured Priors and Application to Denoising of Musical Audio
Abstract--We describe in this paper an audio denoising technique based on sparse linear regression with structured priors. The noisy signal is decomposed as a linear combination of...
Cédric Févotte, Bruno Torrésa...
BIBM
2007
IEEE
162views Bioinformatics» more  BIBM 2007»
14 years 3 months ago
Multiple Interacting Subcellular Structure Tracking by Sequential Monte Carlo Method
With the wide application of green fluorescent protein (GFP) in the study of live cells, there is a surging need for the computer-aided analysis on the huge amount of image seque...
Quan Wen, Jean Gao, Kate Luby-Phelps
JMLR
2010
139views more  JMLR 2010»
13 years 3 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...
ECCV
2002
Springer
14 years 10 months ago
A Markov Chain Monte Carlo Approach to Stereovision
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
Julien Sénégas