Efficient variational inference in large-scale Bayesian compressed sensing

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 1332-1339

  Papandreou, George ^a   Yuille, Alan L ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Korea University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN COMPUTATION; COMPRESSED SENSING; COMPUTATIONAL BOTTLENECKS; DETERMINISTIC APPROACH; ESTIMATION UNCERTAINTIES; FULLY SCALABLE; GAUSSIAN MARKOV RANDOM FIELD; GAUSSIANS; HEAVY-TAILED; IMAGE DEBLURRING; LARGE-SCALE PROBLEM; LATENT VARIABLE; LEARNING MODELS; POINT ESTIMATION; POSTERIOR DISTRIBUTIONS; RANDOM SAMPLE; STANDARD OPTIMIZATION; TECHNICAL CONTRIBUTION; TIME COMPLEXITY; VARIANCE ESTIMATION; VARIATIONAL ALGORITHMS; VARIATIONAL BAYESIAN; VARIATIONAL INFERENCE;

ALGORITHMS; BAYESIAN NETWORKS; ESTIMATION; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); IMAGE ENHANCEMENT; SIGNAL RECONSTRUCTION;

VARIATIONAL TECHNIQUES;

EID: 84856650207     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130406     Document Type: Conference Paper

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