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ICML
2005
IEEE
16 years 5 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
ICML
2005
IEEE
16 years 5 months ago
Intrinsic dimensionality estimation of submanifolds in Rd
We present a new method to estimate the intrinsic dimensionality of a submanifold M in Rd from random samples. The method is based on the convergence rates of a certain U-statisti...
Matthias Hein, Jean-Yves Audibert
ICML
2005
IEEE
16 years 5 months ago
Online learning over graphs
We apply classic online learning techniques similar to the perceptron algorithm to the problem of learning a function defined on a graph. The benefit of our approach includes simp...
Mark Herbster, Massimiliano Pontil, Lisa Wainer
ICML
2005
IEEE
16 years 5 months ago
Adapting two-class support vector classification methods to many class problems
A geometric construction is presented which is shown to be an effective tool for understanding and implementing multi-category support vector classification. It is demonstrated ho...
Simon I. Hill, Arnaud Doucet
ICML
2005
IEEE
16 years 5 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer