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» Approximating Markov Processes by Averaging
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JMLR
2010
125views more  JMLR 2010»
15 years 1 months 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 1 months 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 22 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 8 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