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216
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AGENTS
1998
Springer
15 years 11 months ago
1998
Springer
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
208
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AIPS
2007
15 years 9 months ago
2007
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
190
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CVPR
2000
IEEE
16 years 8 months ago
2000
IEEE
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
191
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CVPR
2003
IEEE
16 years 8 months ago
2003
IEEE
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
219
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ICCV
2005
IEEE
16 years 8 months ago
2005
IEEE
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...