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» Approximating Markov Processes by Averaging
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JMLR
2010
125views more  JMLR 2010»
15 years 28 days ago
Variational methods for Reinforcement Learning
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Thomas Furmston, David Barber
ICML
2003
IEEE
16 years 7 months ago
Exploration in Metric State Spaces
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
Sham Kakade, Michael J. Kearns, John Langford
ICPR
2008
IEEE
16 years 17 days ago
Direct 3-D shape recovery from image sequence based on multi-scale Bayesian network
We propose a new method for recovering a 3-D object shape from an image sequence. In order to recover high-resolution relative depth without using the complex Markov random field...
Norio Tagawa, Junya Kawaguchi, Shoichi Naganuma, K...
3DPVT
2006
IEEE
176views Visualization» more  3DPVT 2006»
16 years 6 days ago
Belief Propagation for Panorama Generation
We present an algorithm for generating panoramic images of complex scenes from a multi-sensor camera. We further present a programmable graphics hardware implementation to process...
Alan Brunton, Chang Shu
IJCAI
2007
15 years 7 months ago
The Value of Observation for Monitoring Dynamic Systems
We consider the fundamental problem of monitoring (i.e. tracking) the belief state in a dynamic system, when the model is only approximately correct and when the initial belief st...
Eyal Even-Dar, Sham M. Kakade, Yishay Mansour