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ICML
2006
IEEE
14 years 5 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
AAAI
2000
13 years 6 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
CORR
2008
Springer
98views Education» more  CORR 2008»
13 years 4 months ago
Information Acquisition and Exploitation in Multichannel Wireless Networks
A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by ...
Sudipto Guha, Kamesh Munagala, Saswati Sarkar
CVPR
2004
IEEE
14 years 6 months ago
High-Zoom Video Hallucination by Exploiting Spatio-Temporal Regularities
In this paper, we consider the problem of super-resolving a human face video by a very high (?16) zoom factor. Inspired by recent literature on hallucination and examplebased lear...
Göksel Dedeoglu, Jonas August, Takeo Kanade
CORR
2011
Springer
261views Education» more  CORR 2011»
12 years 11 months ago
Convex and Network Flow Optimization for Structured Sparsity
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...