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FOCM
2008
140views more  FOCM 2008»
10 years 2 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
ADCM
2006
74views more  ADCM 2006»
10 years 2 months ago
Linearly constrained reconstruction of functions by kernels with applications to machine learning
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
Robert Schaback, J. Werner
CORR
2008
Springer
130views Education» more  CORR 2008»
10 years 2 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...
AUTOMATICA
2010
167views more  AUTOMATICA 2010»
10 years 2 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
ICASSP
2010
IEEE
10 years 2 months ago
Acceleration of sequence kernel computation for real-time speaker identification
The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, T...
NIPS
2003
10 years 4 months ago
Learning to Find Pre-Images
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...
Gökhan H. Bakir, Jason Weston, Bernhard Sch&o...
NIPS
2004
10 years 4 months ago
Supervised Graph Inference
We formulate the problem of graph inference where part of the graph is known as a supervised learning problem, and propose an algorithm to solve it. The method involves the learni...
Jean-Philippe Vert, Yoshihiro Yamanishi
NIPS
2004
10 years 4 months ago
Kernel Methods for Implicit Surface Modeling
We describe methods for computing an implicit model of a hypersurface that is given only by a finite sampling. The methods work by mapping the sample points into a reproducing ker...
Bernhard Schölkopf, Joachim Giesen, Simon Spa...
ESANN
2003
10 years 4 months ago
Kernel PLS variants for regression
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewall...
NIPS
2008
10 years 4 months ago
Regularized Policy Iteration
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csab...
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