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TASLP
2010
142views more  TASLP 2010»
14 years 11 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...
SIAMJO
2010
84views more  SIAMJO 2010»
15 years 2 months ago
A Redistributed Proximal Bundle Method for Nonconvex Optimization
Proximal bundle methods have been shown to be highly successful optimization methods for unconstrained convex problems with discontinuous first derivatives. This naturally leads ...
Warren Hare, Claudia A. Sagastizábal
EMMCVPR
2009
Springer
15 years 11 months ago
Multi-label Moves for MRFs with Truncated Convex Priors
Optimization with graph cuts became very popular in recent years. As more applications rely on graph cuts, different energy functions are being employed. Recent evaluation of optim...
Olga Veksler
IJON
2007
184views more  IJON 2007»
15 years 4 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
NIPS
2004
15 years 5 months ago
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...
Vladimir Koltchinskii, Manel Martínez-Ram&o...