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9 years 10 months ago
Multiple kernel nonnegative matrix factorization
Kernel nonnegative matrix factorization (KNMF) is a recent kernel extension of NMF, where matrix factorization is carried out in a reproducing kernel Hilbert space (RKHS) with a f...
Shounan An, Jeong-Min Yun, Seungjin Choi
114views more  JMLR 2010»
10 years 1 months ago
On the relation between universality, characteristic kernels and RKHS embedding of measures
Universal kernels have been shown to play an important role in the achievability of the Bayes risk by many kernel-based algorithms that include binary classification, regression, ...
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. ...
110views more  JMLR 2010»
10 years 1 months ago
Nonlinear functional regression: a functional RKHS approach
This paper deals with functional regression, in which the input attributes as well as the response are functions. To deal with this problem, we develop a functional reproducing ke...
Hachem Kadri, Emmanuel Duflos, Philippe Preux, St&...
145views more  JMLR 2010»
10 years 1 months ago
Kernel Partial Least Squares is Universally Consistent
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
Gilles Blanchard, Nicole Krämer
143views Neural Networks» more  NN 2008»
10 years 4 months ago
A new nonlinear similarity measure for multichannel signals
We propose a novel similarity measure, called the correntropy coefficient, sensitive to higher order moments of the signal statistics based on a similarity function called the cro...
Jian-Wu Xu, Hovagim Bakardjian, Andrzej Cichocki, ...
101views more  IEICET 2010»
10 years 4 months ago
Irregular Sampling on Shift Invariant Spaces
Let V (φ) be a shift invariant subspace of L2 (R) generated by a Riesz or frame generator φ(t) in L2 (R). We assume that φ(t) is suitably chosen so that V (φ) becomes a reprod...
Kil Hyun Kwon, Jaekyu Lee
160views more  JMLR 2002»
10 years 6 months ago
Kernel Independent Component Analysis
We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On th...
Francis R. Bach, Michael I. Jordan
118views more  PRL 2008»
10 years 6 months ago
A large margin approach for writer independent online handwriting classification
This paper proposes a new approach for classifying multivariate time-series with applications to the problem of writer independent online handwritten character recognition. Each t...
Karthik Kumara, Rahul Agrawal, Chiranjib Bhattacha...
143views more  JMLR 2006»
10 years 6 months ago
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...
Régis Vert, Jean-Philippe Vert
97views more  FOCM 2006»
10 years 6 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou