2914 search results - page 280 / 583 » Learning and Inference with Constraints |
180
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CORR
2010
Springer
15 years 5 months ago
2010
Springer
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
217
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ICCV
2011
IEEE
14 years 6 months ago
2011
IEEE
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
177
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DAC
2006
ACM
16 years 7 months ago
2006
ACM
Design and verification of systems at the Register-Transfer (RT) or behavioral level require the ability to reason at higher levels of abstraction. Difference logic consists of an...
203
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IJCAI
1997
15 years 8 months ago
1997
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
187
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CVPR
1999
IEEE
16 years 8 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...