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KI
2010
Springer
11 years 3 months ago
Soft Evidential Update via Markov Chain Monte Carlo Inference
The key task in probabilistic reasoning is to appropriately update one’s beliefs as one obtains new information in the form of evidence. In many application settings, however, th...
Dominik Jain, Michael Beetz
JCNS
2010
104views more  JCNS 2010»
11 years 3 months ago
A new look at state-space models for neural data
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
ICASSP
2010
IEEE
11 years 3 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, ...
CP
2010
Springer
11 years 3 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
PAMI
2007
196views more  PAMI 2007»
11 years 4 months ago
Bayesian Analysis of Lidar Signals with Multiple Returns
—Time-Correlated Single Photon Counting and Burst Illumination Laser data can be used for range profiling and target classification. In general, the problem is to analyze the res...
Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J...
IVC
2008
141views more  IVC 2008»
11 years 4 months ago
Segmentation of color images via reversible jump MCMC sampling
Reversible jump Markov chain Monte Carlo (RJMCMC) is a recent method which makes it possible to construct reversible Markov chain samplers that jump between parameter subspaces of...
Zoltan Kato
TASLP
2002
109views more  TASLP 2002»
11 years 5 months ago
Particle methods for Bayesian modeling and enhancement of speech signals
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, S...
TWC
2008
107views more  TWC 2008»
11 years 5 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...
PAMI
2008
137views more  PAMI 2008»
11 years 5 months ago
Tracking the Visual Focus of Attention for a Varying Number of Wandering People
In this article, we define and address the problem of finding the visual focus of attention for a varying number of wandering people (VFOA-W)
Kevin Smith, Sileye O. Ba, Jean-Marc Odobez, Danie...
PAMI
2008
188views more  PAMI 2008»
11 years 5 months ago
Segmentation and Tracking of Multiple Humans in Crowded Environments
Segmentation and tracking of multiple humans in crowded situations is made difficult by interobject occlusion. We propose a model-based approach to interpret the image observations...
Tao Zhao, Ramakant Nevatia, Bo Wu
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