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TSP
2008
89views more  TSP 2008»
14 years 11 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe
NIPS
2008
15 years 1 months ago
Kernel Change-point Analysis
We introduce a kernel-based method for change-point analysis within a sequence of temporal observations. Change-point analysis of an unlabelled sample of observations consists in,...
Zaïd Harchaoui, Francis Bach, Eric Moulines
TIP
2010
141views more  TIP 2010»
14 years 6 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
ICASSP
2011
IEEE
14 years 3 months ago
Polytope kernel density estimates on Delaunay graphs
We present a polytope-kernel density estimation (PKDE) methodology that allows us to perform exact mean-shift updates along the edges of the Delaunay graph of the data. We discuss...
Erhan Bas, Deniz Erdogmus
COLT
2004
Springer
15 years 5 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