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» Nonlinear Component Analysis as a Kernel Eigenvalue Problem
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ICA
2010
Springer
14 years 9 months ago
Non-negative Independent Component Analysis Algorithm Based on 2D Givens Rotations and a Newton Optimization
Abstract. In this paper, we consider the Independent Component Analysis problem when the hidden sources are non-negative (Non-negative ICA). This problem is formulated as a non-lin...
Wendyam Serge Boris Ouedraogo, Antoine Souloumiac,...
105
Voted
TSP
2012
13 years 7 months ago
Parametrization of Linear Systems Using Diffusion Kernels
—Modeling natural and artificial systems has played a key role in various applications and has long been a task that has drawn enormous efforts. In this work, instead of explori...
Ronen Talmon, Dan Kushnir, Ronald R. Coifman, Isra...
JMLR
2006
131views more  JMLR 2006»
14 years 11 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser
105
Voted
NIPS
2003
15 years 1 months ago
Eigenvoice Speaker Adaptation via Composite Kernel PCA
Eigenvoice speaker adaptation has been shown to be effective when only a small amount of adaptation data is available. At the heart of the method is principal component analysis (...
James T. Kwok, Brian Mak, Simon Ho
108
Voted
NIPS
2003
15 years 1 months ago
Learning to Find Pre-Images
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...
Gökhan H. Bakir, Jason Weston, Bernhard Sch&o...