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UAI
2004
13 years 8 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
CVPR
2005
IEEE
14 years 9 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black
GLOBECOM
2009
IEEE
14 years 2 months ago
Random Linear Network Coding for Time-Division Duplexing: Field Size Considerations
Abstract— We study the effect of the field size on the performance of random linear network coding for time division duplexing channels proposed in [1]. In particular, we study ...
Daniel Enrique Lucani, Muriel Médard, Milic...
CVPR
2005
IEEE
13 years 9 months ago
Dense Photometric Stereo Using Tensorial Belief Propagation
We address the normal reconstruction problem by photometric stereo using a uniform and dense set of photometric images captured at fixed viewpoint. Our method is robust to spurio...
Kam-Lun Tang, Chi-Keung Tang, Tien-Tsin Wong
CVPR
2011
IEEE
13 years 2 months ago
Learning Context for Collective Activity Recognition
In this paper we present a framework for the recognition of collective human activities. A collective activity is defined or reinforced by the existence of coherent behavior of i...
Wongun Choi, Silvio Savarese, Khuram Shahid