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This paper considers the problem of estimating an unknown high dimensional signal from noisy linear measurements, {when} the signal is assumed to possess a \emph{group-sparse} structure in a {known,} fixed dictionary.
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Y. Nardi and A. Rinaldo, · 2008
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S. Negahban, B. Yu, M. J. Wainwright, and P. K. Ravikumar, · 2009
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E. J. Candès and Y. Plan, · 2009
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“Estimation consistency of the group Lasso and its applications,”
H. Liu and J. Zhang, · 2009
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“On the reconstruction of block-sparse signals with an optimal number of measurements,”
M. Stojnic, F. Parvaresh, and B. Hassibi, · 2009
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“Robust recovery of signals from a structured union of subspaces,”
Y. C. Eldar and M. Mishali, · 2009
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“Anomaly detection: A survey,”
V. Chandola, A. Banerjee, and V. Kumar, · 2009
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“Sharp thresholds for high-dimensional and noisy sparsity recovery using ℓ 1 \ell_{1} -constrained quadratic programming (Lasso),”
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J. Huang and T. Zhang, · 2010
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“Average case analysis of multichannel sparse recovery using convex relaxation,”
Y. C. Eldar and H. Rauhut, · 2010
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Y. C. Eldar, P. Kuppinger, and H. Bölcskei, · 2010
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“Subspace methods for joint sparse recovery,”
K. Lee, Y. Bresler, and M. Junge, · 2012
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E. Elhamifar and R. Vidal, · 2012
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N. S. Rao, B. Recht, and R. D. Nowak, · 2012
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M. F. Duarte, M. B. Wakin, D. Baron, S. Sarvotham, and R. G. Baraniuk, · 2013
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A. S. Bandeira, E. Dobriban, D. G. Mixon, and W. F. Sawin, · 2013
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“Hanson-Wright inequality and sub-gaussian concentration,”
M. Rudelson and R. Vershynin, · 2013
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R. G. Baraniuk, V. Cevher, M. F. Duarte, and C. Hegde, · 2010
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“ ℓ 2 / ℓ 1 \ell_{2}/\ell_{1} -optimization in block-sparse compressed sensing and its strong thresholds,”
M. Stojnic, · 2010
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“Support union recovery in high-dimensional multivariate regression,”
G. Obozinski, M. J. Wainwright, and M. I. Jordan, · 2011
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“Union support recovery in multi-task learning,”
M. Kolar, J. Lafferty, and L. Wasserman, · 2011
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“Sparse group selection through co-adaptive penalties,”
Z. Fang, · 2011
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“Oracle inequalities and optimal inference under group sparsity,”
K. Lounici, M. Pontil, S. Van De Geer, and A. B. Tsybakov, · 2011
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“Living on the edge: Phase transitions in convex programs with random data,”
D. Amelunxen, M. Lotz, M. B. McCoy, and J. A. Tropp, · 2014
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“Corrupted sensing: Novel guarantees for separating structured signals,”
R. Foygel and L. Mackey, · 2014
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“Block-sparse reconstruction and imaging for lamb wave structural health monitoring,”
R. Levine and J. E. Michaels, · 2014
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“On the linear convergence of the approximate proximal splitting method for non-smooth convex optimization,”
M. Kadkhodaie, M. Sanjabi, and Z-Q Luo, · 2014
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“Conditioning of random block subdictionaries with applications to block-sparse recovery and regression,”
W. U. Bajwa, M. F. Duarte, and R. Calderbank, · 2015
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“Anomaly-sensitive dictionary learning for structural diagnostics from ultrasonic wavefields,”
J. Druce, J. D. Haupt, and S. Gonella, · 2015
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“On block coherence of frames,”
R. Calderbank, A. Thompson, and Y. Xie, · 2015
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“Defect triangulation via demixing algorithms based on dictionaries with different morphological complexity,”
J. Druce, S. Gonella, M. Kadkhodaie, S. Jain, and J. D. Haupt, · 2016
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“Multimodal sparse reconstruction in guided wave imaging of defects in plates,”
A. Golato, S. Santhanam, F. Ahmad, and M. G. Amin, · 2016
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“Error bounds for compressed sensing algorithms with group sparsity: A unified approach,”
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“Group-level support recovery guarantees for group Lasso estimator,”
M. K. Elyaderani, S. Jain, J. Druce, S. Gonella, and J. Haupt, · 2017
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