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» Network Flow Algorithms for Structured Sparsity
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CORR
2010
Springer
167views Education» more  CORR 2010»
13 years 11 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...
CORR
2011
Springer
261views Education» more  CORR 2011»
13 years 6 months ago
Convex and Network Flow Optimization for Structured Sparsity
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...
ICASSP
2011
IEEE
13 years 2 months ago
Decentralized support detection of multiple measurement vectors with joint sparsity
This paper considers the problem of finding sparse solutions from multiple measurement vectors (MMVs) with joint sparsity. The solutions share the same sparsity structure, and th...
Qing Ling, Zhi Tian
PLDI
1994
ACM
14 years 3 months ago
The Program Structure Tree: Computing Control Regions in Linear Time
In this paper, we describe the program structure tree (PST), a hierarchical representation of program structure based on single entry single exit (SESE) regions of the control flo...
Richard Johnson, David Pearson, Keshav Pingali
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 5 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang