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CDC
2008
IEEE
125views Control Systems» more  CDC 2008»
14 years 2 months 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 10 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, ...
ACL
2011
12 years 11 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
171views Education» more  CORR 2010»
13 years 8 months ago
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...
TIP
2011
123views more  TIP 2011»
13 years 2 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz