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» Learning the Structure of Deep Sparse Graphical Models
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ECCV
2002
Springer
14 years 10 months ago
Audio-Video Sensor Fusion with Probabilistic Graphical Models
Abstract. We present a new approach to modeling and processing multimedia data. This approach is based on graphical models that combine audio and video variables. We demonstrate it...
Matthew J. Beal, Hagai Attias, Nebojsa Jojic
ECCV
2008
Springer
14 years 10 months ago
Learning Two-View Stereo Matching
We propose a graph-based semi-supervised symmetric matching framework that performs dense matching between two uncalibrated wide-baseline images by exploiting the results of sparse...
Jianxiong Xiao, Jingni Chen, Dit-Yan Yeung, Long Q...
JMLR
2000
134views more  JMLR 2000»
13 years 8 months ago
Learning with Mixtures of Trees
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
Marina Meila, Michael I. Jordan
ICASSP
2011
IEEE
13 years 12 days ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
ICML
2007
IEEE
14 years 9 months ago
Modeling changing dependency structure in multivariate time series
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
Xiang Xuan, Kevin P. Murphy