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» Frame domain signal processing: Framework and applications
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108
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JAIR
2000
152views more  JAIR 2000»
15 years 9 days ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
73
Voted
ICA
2010
Springer
15 years 21 days ago
Double Sparsity: Towards Blind Estimation of Multiple Channels
We propose a framework for blind multiple filter estimation from convolutive mixtures, exploiting the time-domain sparsity of the mixing filters and the disjointness of the sources...
Prasad Sudhakar, Simon Arberet, Rémi Gribon...
ICASSP
2011
IEEE
14 years 4 months ago
Bayesian reinforcement learning for POMDP-based dialogue systems
Spoken dialogue systems are gaining popularity with improvements in speech recognition technologies. Dialogue systems can be modeled effectively using POMDPs, achieving improvemen...
ShaoWei Png, Joelle Pineau
110
Voted
JAIR
2006
110views more  JAIR 2006»
15 years 15 days ago
Domain Adaptation for Statistical Classifiers
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Hal Daumé III, Daniel Marcu
DATE
2010
IEEE
155views Hardware» more  DATE 2010»
15 years 5 months ago
Scheduling and energy-distortion tradeoffs with operational refinement of image processing
— Ubiquitous image processing tasks (such as transform decompositions, filtering and motion estimation) do not currently provide graceful degradation when their clock-cycles budg...
Davide Anastasia, Yiannis Andreopoulos