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138
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ECML
2006
Springer
15 years 7 months ago
Combinatorial Markov Random Fields
Abstract. A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatoria...
Ron Bekkerman, Mehran Sahami, Erik G. Learned-Mill...
137
Voted
IJCAI
2007
15 years 5 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
148
Voted
NIPS
2008
15 years 5 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
151
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ICCV
2005
IEEE
15 years 9 months ago
Automatic 3D Face Modeling from Video
In this paper, we develop an efficient technique for fully automatic recovery of accurate 3D face shape from videos captured by a low cost camera. The method is designed to work ...
Le Xin, Qiang Wang, Jianhua Tao, Xiaoou Tang, Tien...
133
Voted
IJCV
2000
195views more  IJCV 2000»
15 years 3 months ago
Optical Flow Constraints on Deformable Models with Applications to Face Tracking
Optical flow provides a constraint on the motion of a deformable model. We derive and solve a dynamic system incorporating flow as a hard constraint, producing a model-based least...
Douglas DeCarlo, Dimitris N. Metaxas