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» A Hilbert Space Embedding for Distributions
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STOC
2003
ACM
102views Algorithms» more  STOC 2003»
14 years 6 months ago
On metric ramsey-type phenomena
The main question studied in this article may be viewed as a nonlinear analogue of Dvoretzky's theorem in Banach space theory or as part of Ramsey theory in combinatorics. Gi...
Yair Bartal, Nathan Linial, Manor Mendel, Assaf Na...
CORR
2008
Springer
130views Education» more  CORR 2008»
13 years 6 months ago
A Kernel Method for the Two-Sample Problem
We propose two statistical tests to determine if two samples are from different distributions. Our test statistic is in both cases the distance between the means of the two sample...
Arthur Gretton, Karsten M. Borgwardt, Malte J. Ras...
ICML
2008
IEEE
14 years 7 months ago
Metric embedding for kernel classification rules
In this paper, we consider a smoothing kernelbased classification rule and propose an algorithm for optimizing the performance of the rule by learning the bandwidth of the smoothi...
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G....
AUTOMATICA
2010
167views more  AUTOMATICA 2010»
13 years 6 months ago
A new kernel-based approach for linear system identification
This paper describes a new kernel-based approach for linear system identification of stable systems. We model the impulse response as the realization of a Gaussian process whose s...
Gianluigi Pillonetto, Giuseppe De Nicolao
JMLR
2002
160views more  JMLR 2002»
13 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