Publications related to A Catalyst Framework for Minimax Optimization

Online-Batch Strongly Convex Multi Kernel Learning

Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled ap- proach to combine multiple cues, and to obtain state-of-the- art performance. A general drawback of these strategies is the high computational co ...

Idiap2010

Online-Batch Strongly Convex Multi Kernel Learning

Barbara Caputo, Jie Luo

Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled ap- proach to combine multiple cues, and to obtain state-of-the- art performance. A general drawback of these strategies is the high computational co ...

2010

A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution

Michaël Unser, Cédric René Jean Vonesch

We present a fast variational deconvolution algorithm that minimizes a quadratic data term subject to a regularization on the

\ell ^{ 1 }

-norm of the wavelet coefficients of the solution. Previously available methods have essentially consisted in alte ...

IEEE2008

Modules d'endo-p-permutation

Jean-Marie Urfer

This dissertation is concerned with the study of a new family of representations of finite groups, the endo-p-permutation modules. Given a prime number p, a finite group G of order divisible by p and an algebraically closed field k of characteristic p, we ...

EPFL2006

Distance transformations: fast algorithms and applications to medical image processing

Olivier Cuisenaire

Medical image processing is a demanding domain, both in terms of CPU and memory requirements. The volume of data to be processed is often large (a typical MRI dataset requires 10 MBytes) and many processing tools are only useful to the physician if they ar ...

1999

A Catalyst Framework for Minimax Optimization

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Online-Batch Strongly Convex Multi Kernel Learning

Online-Batch Strongly Convex Multi Kernel Learning

A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution

Modules d'endo-p-permutation

Distance transformations: fast algorithms and applications to medical image processing

Online-Batch Strongly Convex Multi Kernel Learning

A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution

Online-Batch Strongly Convex Multi Kernel Learning

Modules d'endo-p-permutation

Distance transformations: fast algorithms and applications to medical image processing