On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy
Linear Measurements

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On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements

IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2013

18 June 2013

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Papers citing "On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements"

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Title
Active Search for Sparse Signals with Region Sensing Yifei Ma Roman Garnett J. Schneider 223 13 0 02 Dec 2016
Noisy Inductive Matrix Completion Under Sparse Factor Models Akshay Soni T. Chevalier Swayambhoo Jain 182 10 0 13 Sep 2016
Leveraging Union of Subspace Structure to Improve Constrained Clustering J. Lipor Laura Balzano 153 17 0 06 Aug 2016
Sequential Information Guided Sensing Ruiyang Song Yao Xie Sebastian Pokutta 134 0 0 01 Sep 2015
On Convolutional Approximations to Linear Dimensionality Reduction Operators for Large Scale Data Processing Swayambhoo Jain Jarvis Haupt 158 2 0 25 Feb 2015
Info-Greedy sequential adaptive compressed sensingIEEE Journal on Selected Topics in Signal Processing (JSTSP), 2014 Gábor Braun Sebastian Pokutta Yao Xie 315 34 0 02 Jul 2014
Identifying Outliers in Large Matrices via Randomized Adaptive Compressive SamplingIEEE Transactions on Signal Processing (IEEE TSP), 2014 Xingguo Li Jarvis Haupt 382 59 0 01 Jul 2014
Recovering Graph-Structured Activations using Adaptive Compressive MeasurementsAsilomar Conference on Signals, Systems and Computers (ACSSC), 2013 A. Krishnamurthy James Sharpnack Aarti Singh 322 21 0 01 May 2013