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Several learning applications require solving high-dimensional regression problems where the relevant features belong to a small number of (overlapping) groups.
An analysis of approximations for maximizing submodular set functions
George L Nemhauser, Laurence A Wolsey, and Marshall L Fisher · 1978
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Signal recovery from random measurements via orthogonal matching pursuit
Joel Tropp, Anna C Gilbert, et al · 2007
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Sampling theorems for signals from the union of finite-dimensional linear subspaces
Thomas Blumensath and Mike E Davies · 2009
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Group lasso with overlap and graph lasso
Laurent Jacob, Guillaume Obozinski, and Jean-Philippe Vert · 2009
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Taking advantage of sparsity in multi-task learning
Karim Lounici, Massimiliano Pontil, Alexandre B Tsybakov, and Sara Van De Geer · 2009
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Grouped orthogonal matching pursuit for variable selection and prediction
Grzegorz Swirszcz, Naoki Abe, and Aurelie C Lozano · 2009
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On the conditions used to prove oracle results for the lasso
Sara A Van De Geer, Peter Bühlmann, et al · 2009
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Convex analysis and optimization with submodular functions: A tutorial
Francis Bach · 2010
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Model-based compressive sensing
Richard G Baraniuk, Volkan Cevher, Marco F Duarte, and Chinmay Hegde · 2010
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Normalized iterative hard thresholding: Guaranteed stability and performance
Thomas Blumensath and Mike E Davies · 2010
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Proximal methods for sparse hierarchical dictionary learning
Rodolphe Jenatton, Julien Mairal, Francis R Bach, and Guillaume R Obozinski · 2010
Cited alongside, same era.
Sampling and reconstructing signals from a union of linear subspaces
Thomas Blumensath · 2011
Cited alongside, same era.
Learning with structured sparsity
Junzhou Huang, Tong Zhang, and Dimitris Metaxas · 2011
Cited alongside, same era.
Orthogonal matching pursuit with replacement
Prateek Jain, Ambuj Tewari, and Inderjit S Dhillon · 2011
Cited alongside, same era.
Combinatorial selection and least absolute shrinkage via the clash algorithm
Anastasios Kyrillidis and Volkan Cevher · 2012
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Universal measurement bounds for structured sparse signal recovery
Nikhil S Rao, Ben Recht, and Robert D Nowak · 2012
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Tractability of interpretability via selection of group-sparse models
Nirav Bhan, Luca Baldassarre, and Volkan Cevher · 2013
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Sparse overlapping sets lasso for multitask learning and its application to fmri analysis
Nikhil Rao, Christopher Cox, Rob Nowak, and Timothy T Rogers · 2013
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On iterative hard thresholding methods for high-dimensional m-estimation
Prateek Jain, Ambuj Tewari, and Purushottam Kar · 2014
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Gradient hard thresholding pursuit for sparsity-constrained optimization
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Iterative projections for signal identification on manifolds: Global recovery guarantees
Parikshit Shah and Venkat Chandrasekaran · 2011
Cited alongside, same era.
Greedy algorithms for structurally constrained high dimensional problems
Ambuj Tewari, Pradeep K Ravikumar, and Inderjit S Dhillon · 2011
Cited alongside, same era.
Xiaotong Yuan, Ping Li, and Tong Zhang · 2014
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Approximation algorithms for model-based compressive sensing
Chinmay Hegde, Piotr Indyk, and Ludwig Schmidt · 2015
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Forward–backward greedy algorithms for atomic norm regularization
Nikhil Rao, Parikshit Shah, and Stephen Wright · 2015
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