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Highly Cited

2011

Highly Cited

2011

This book provides a largely self-contained account of the main results of convex analysis and optimization in Hilbert space. A… Expand

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Highly Cited

2007

Highly Cited

2007

We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach… Expand

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Highly Cited

2005

Highly Cited

2005

Several methods for solving systems of equilibrium problems in Hilbert spaces – and for finding best approximations thereof – are… Expand

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Highly Cited

2004

Highly Cited

2004

1 Theory.- 2 RKHS AND STOCHASTIC PROCESSES.- 3 Nonparametric Curve Estimation.- 4 Measures And Random Measures.- 5 Miscellaneous… Expand

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Highly Cited

2004

Highly Cited

2004

We propose a novel method of dimensionality reduction for supervised learning problems. Given a regression or classification… Expand

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Highly Cited

2004

Highly Cited

2004

This paper describes the Jensen-Shannon divergence (JSD) and Hilbert space embedding. With natural definitions making these… Expand

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Highly Cited

2001

Highly Cited

2001

A family of regularized least squares regression models in a Reproducing Kernel Hilbert Space is extended by the kernel partial… Expand

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Highly Cited

2001

Highly Cited

2001

Several schemes for the linear mapping of a multidimensional space have been proposed for various applications, such as access… Expand

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Highly Cited

1966

Highly Cited

1966

The purpose of this note is to show that a close relationship exists between the notions of majorization, factorization, and… Expand

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Highly Cited

1964

Highly Cited

1964

This note gives a construction for minimizing certain twice-differentiable functions on a closed convex subset C, of a Hubert… Expand

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