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ICANN
2009
Springer
15 years 1 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 1 months ago
Towards estimating nadir objective vector using evolutionary approaches
Nadir point plays an important role in multi-objective optimization because of its importance in estimating the range of objective values corresponding to desired Pareto-optimal s...
Kalyanmoy Deb, Shamik Chaudhuri, Kaisa Miettinen
AAAI
1998
14 years 11 months ago
Bayesian Q-Learning
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
Richard Dearden, Nir Friedman, Stuart J. Russell
ECCV
2004
Springer
15 years 3 months ago
A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection
This paper deals with the computation of optical flow and occlusion detection in the case of large displacements. We propose a Bayesian approach to the optical flow problem and s...
Christoph Strecha, Rik Fransens, Luc J. Van Gool
3DIM
2007
IEEE
15 years 4 months ago
A Bayesian Framework for Simultaneous Matting and 3D Reconstruction
Conventional approaches to 3D scene reconstruction often treat matting and reconstruction as two separate problems, with matting a prerequisite to reconstruction. The problem with...
Jean-Yves Guillemaut, Adrian Hilton, Jonathan Star...