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» A Markov Chain Monte Carlo Approach to Stereovision
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CSDA
2007
94views more  CSDA 2007»
13 years 7 months ago
Some extensions of score matching
Many probabilistic models are only defined up to a normalization constant. This makes maximum likelihood estimation of the model parameters very difficult. Typically, one then h...
Aapo Hyvärinen
ML
2006
ACM
13 years 7 months ago
Using duration models to reduce fragmentation in audio segmentation
We investigate explicit segment duration models in addressing the problem of fragmentation in musical audio segmentation. The resulting probabilistic models are optimised using Mar...
Samer A. Abdallah, Mark B. Sandler, Christophe Rho...
TWC
2008
107views more  TWC 2008»
13 years 7 months ago
A low complexity user scheduling algorithm for uplink multiuser MIMO systems
A low complexity user scheduling algorithm based on a novel adaptive Markov chain Monte Carlo (AMCMC) method is proposed to achieve the maximal sum capacity in an uplink multiple-i...
Yangyang Zhang, Chunlin Ji, Yi Liu, Wasim Q. Malik...
CP
2010
Springer
13 years 6 months ago
Computing the Density of States of Boolean Formulas
Abstract. In this paper we consider the problem of computing the density of states of a Boolean formula in CNF, a generalization of both MAX-SAT and model counting. Given a Boolean...
Stefano Ermon, Carla P. Gomes, Bart Selman
ICASSP
2010
IEEE
13 years 6 months ago
A partially collapsed Gibbs sampler for parameters with local constraints
We consider Bayesian detection/classification of discrete random parameters that are strongly dependent locally due to some deterministic local constraint. Based on the recently ...
Georg Kail, Jean-Yves Tourneret, Franz Hlawatsch, ...