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CDC
2008
IEEE
125views Control Systems» more  CDC 2008»
14 years 7 days ago
Dynamical structure analysis of sparsity and minimality heuristics for reconstruction of biochemical networks
— Network reconstruction, i.e. obtaining network structure from input-output information, is a central theme in systems biology. A variety of approaches aim to obtaining structur...
Russell Howes, Lee John Eccleston, Jorge M. Goncal...
JMLR
2012
11 years 8 months ago
A General Framework for Structured Sparsity via Proximal Optimization
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
ICML
2010
IEEE
13 years 6 months ago
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
Seyoung Kim, Eric P. Xing
ACL
2011
12 years 9 months ago
Discovering Sociolinguistic Associations with Structured Sparsity
We present a method to discover robust and interpretable sociolinguistic associations from raw geotagged text data. Using aggregate demographic statistics about the authors’ geo...
Jacob Eisenstein, Noah A. Smith, Eric P. Xing
CORR
2010
Springer
167views Education» more  CORR 2010»
13 years 5 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...