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» Bayesian Parameter Estimation: A Monte Carlo Approach
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DPHOTO
2009
138views Hardware» more  DPHOTO 2009»
14 years 9 months ago
Statistical identification and analysis of defect development in digital imagers
The lifetime of solid-state image sensors is limited by the appearance of defects, particularly hot-pixels, which we have previously shown to develop continuously over the sensor ...
Jenny Leung, Glenn H. Chapman, Zahava Koren, Israe...
AAAI
2010
15 years 1 months ago
Reinforcement Learning via AIXI Approximation
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
NECO
2008
134views more  NECO 2008»
14 years 11 months ago
Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach
One of the central problems in cognitive science is determining the mental representations that underlie human inferences. Solutions to this problem often rely on the analysis of ...
Daniel J. Navarro, Thomas L. Griffiths
FSS
2008
87views more  FSS 2008»
14 years 12 months ago
Representing parametric probabilistic models tainted with imprecision
Numerical possibility theory, belief function have been suggested as useful tools to represent imprecise, vague or incomplete information. They are particularly appropriate in unc...
Cédric Baudrit, Didier Dubois, Nathalie Per...
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 6 months ago
Bayesian estimation of rule accuracy in UCS
Learning Classifier Systems differ from many other classification techniques, in that new rules are constantly discovered and evaluated. This feature of LCS gives rise to an im...
James A. R. Marshall, Gavin Brown, Tim Kovacs