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CORR
2010
Springer
167views Education» more  CORR 2010»
9 years 1 months ago
Network Flow Algorithms for Structured Sparsity
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...
ATMOS
2007
138views Optimization» more  ATMOS 2007»
9 years 3 months ago
A new concept of robustness
In this paper a new concept of robustness is introduced and the corresponding optimization problem is stated. This new concept is applied to transportation network designs in which...
Ricardo García, Ángel Marín, ...
ICASSP
2009
IEEE
9 years 8 months ago
Robust-SL0 for stable sparse representation in noisy settings
In the last few years, we have witnessed an explosion in applications of sparse representation, the majority of which share the need for finding sparse solutions of underdetermine...
Armin Eftekhari, Massoud Babaie-Zadeh, Christian J...
ICML
2004
IEEE
10 years 2 months ago
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
ICML
2007
IEEE
10 years 2 months ago
Supervised clustering of streaming data for email batch detection
We address the problem of detecting batches of emails that have been created according to the same template. This problem is motivated by the desire to filter spam more effectivel...
Peter Haider, Ulf Brefeld, Tobias Scheffer
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