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» Kernel methods and the exponential family
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ALT
2005
Springer
14 years 4 months ago
Measuring Statistical Dependence with Hilbert-Schmidt Norms
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
Arthur Gretton, Olivier Bousquet, Alex J. Smola, B...
FGR
2008
IEEE
255views Biometrics» more  FGR 2008»
14 years 1 months ago
Aligned Cluster Analysis for temporal segmentation of human motion
Temporal segmentation of human motion into actions is a crucial step for understanding and building computational models of human motion. Several issues contribute to the challeng...
Feng Zhou, Fernando De la Torre, Jessica K. Hodgin...
SIAMMA
2011
97views more  SIAMMA 2011»
12 years 10 months ago
Convergence Rates for Greedy Algorithms in Reduced Basis Methods
The reduced basis method was introduced for the accurate online evaluation of solutions to a parameter dependent family of elliptic partial differential equations. ly, it can be ...
Peter Binev, Albert Cohen, Wolfgang Dahmen, Ronald...
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 11 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa