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APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
14 years 12 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan
CVPR
2009
IEEE
15 years 8 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
CVPR
2010
IEEE
15 years 2 months ago
A Novel Markov Random Field Based Deformable Model for Face Recognition
In this paper, a new scheme to address the face recognition problem is proposed. Different from traditional face recognition approaches which represent each facial image by a sing...
Shu Liao, Albert C.S. Chung
CDC
2008
IEEE
184views Control Systems» more  CDC 2008»
15 years 4 months ago
Almost sure convergence to consensus in Markovian random graphs
— In this paper we discuss the consensus problem for a network of dynamic agents with undirected information flow and random switching topologies. The switching is determined by...
Ion Matei, Nuno C. Martins, John S. Baras
ICCS
2001
Springer
15 years 2 months ago
On Parallel Pseudo-Random Number Generation
Parallel computing has been touted as the pinnacle of high performance digital computing by many. However, many problems remain intractable using deterministic algorithms. Randomiz...
Chih Jeng Kenneth Tan