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ALT
2007
Springer
14 years 5 months ago
Online Regression Competitive with Changing Predictors
This paper deals with the problem of making predictions in the online mode of learning where the dependence of the outcome yt on the signal xt can change with time. The Aggregating...
Steven Busuttil, Yuri Kalnishkan
ICML
2009
IEEE
14 years 11 months ago
SimpleNPKL: simple non-parametric kernel learning
Previous studies of Non-Parametric Kernel (NPK) learning usually reduce to solving some Semi-Definite Programming (SDP) problem by a standard SDP solver. However, time complexity ...
Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi
NIPS
2004
14 years 8 days ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 11 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
ALT
2002
Springer
14 years 7 months ago
On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum
Abstract. In this paper we analyze the relationships between the eigenvalues of the m × m Gram matrix K for a kernel k(·, ·) corresponding to a sample x1, . . . , xm drawn from ...
John Shawe-Taylor, Christopher K. I. Williams, Nel...