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TASLP
2010
142views more  TASLP 2010»
13 years 4 months ago
Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation
We consider the problem of extracting the source signals from an under-determined convolutive mixture assuming known mixing filters. State-of-the-art methods operate in the time-fr...
M. Kowalski, Emmanuel Vincent, Rémi Gribonv...
CVPR
2011
IEEE
13 years 1 months ago
Connecting Non-Quadratic Variational Models and MRFs
Spatially-discrete Markov random fields (MRFs) and spatially-continuous variational approaches are ubiquitous in low-level vision, including image restoration, segmentation, opti...
Kevin Schelten, Stefan Roth
ATAL
2007
Springer
14 years 4 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
BMCBI
2006
190views more  BMCBI 2006»
13 years 10 months ago
SNPs3D: Candidate gene and SNP selection for association studies
Background: The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and databas...
Peng Yue, Eugene Melamud, John Moult
JCB
2006
107views more  JCB 2006»
13 years 9 months ago
Maximum Likelihood Molecular Clock Comb: Analytic Solutions
Maximum likelihood (ML) is increasingly used as an optimality criterion for selecting evolutionary trees, but finding the global optimum is a hard computational task. Because no g...
Benny Chor, Amit Khetan, Sagi Snir