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» Step Size Adaptation in Reproducing Kernel Hilbert Space
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JMLR
2006
116views more  JMLR 2006»
13 years 4 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
ADCM
2007
114views more  ADCM 2007»
13 years 4 months ago
Convergence analysis of online algorithms
In this paper, we are interested in the analysis of regularized online algorithms associated with reproducing kernel Hilbert spaces. General conditions on the loss function and st...
Yiming Ying
FOCM
2008
140views more  FOCM 2008»
13 years 4 months ago
Online Gradient Descent Learning Algorithms
This paper considers the least-square online gradient descent algorithm in a reproducing kernel Hilbert space (RKHS) without explicit regularization. We present a novel capacity i...
Yiming Ying, Massimiliano Pontil
TSD
2010
Springer
13 years 2 months ago
Correlation Features and a Linear Transform Specific Reproducing Kernel
Abstract. In this paper we introduce two ideas for phoneme classification: First, we derive the necessary steps to integrate linear transform into the computation of reproducing ke...
Andreas Beschorner, Dietrich Klakow
DIS
2007
Springer
13 years 10 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...