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» On Kernel Methods for Relational Learning
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ICASSP
2011
IEEE
14 years 1 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
59
Voted
ICA
2004
Springer
15 years 3 months ago
Blind Deconvolution Using the Relative Newton Method
We propose a relative optimization framework for quasi maximum likelihood blind deconvolution and the relative Newton method as its particular instance. Special Hessian structure a...
Alexander M. Bronstein, Michael M. Bronstein, Mich...
71
Voted
IJCV
2007
208views more  IJCV 2007»
14 years 9 months ago
Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes
We derive a family of kernels on dynamical systems by applying the Binet-Cauchy theorem to trajectories of states. Our derivation provides a unifying framework for all kernels on d...
S. V. N. Vishwanathan, Alexander J. Smola, Ren&eac...
JMLR
2006
143views more  JMLR 2006»
14 years 9 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
COLT
2004
Springer
15 years 3 months ago
A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra
Abstract. The Gram matrix plays a central role in many kernel methods. Knowledge about the distribution of eigenvalues of the Gram matrix is useful for developing appropriate model...
David C. Hoyle, Magnus Rattray