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COLT
2003
Springer
14 years 21 days ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik
ECML
2007
Springer
14 years 1 months ago
Source Separation with Gaussian Process Models
In this paper we address a method of source separation in the case where sources have certain temporal structures. The key contribution in this paper is to incorporate Gaussian pro...
Sunho Park, Seungjin Choi
ML
2006
ACM
113views Machine Learning» more  ML 2006»
14 years 1 months ago
A separate compilation extension to standard ML
We present an extension to Standard ML, called SMLSC, to support separate compilation. The system gives meaning to individual program fragments, called units. Units may depend on ...
David Swasey, Tom Murphy VII, Karl Crary, Robert H...
COLT
2008
Springer
13 years 9 months ago
On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Shai Shalev-Shwartz, Yoram Singer
IJON
2008
158views more  IJON 2008»
13 years 7 months ago
An adaptive stereo basis method for convolutive blind audio source separation
We consider the problem of convolutive blind source separation of stereo mixtures. This is often tackled using frequency-domain independent component analysis (FDICA), or time-fre...
Maria G. Jafari, Emmanuel Vincent, Samer A. Abdall...