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CORR
2010
Springer
130views Education» more  CORR 2010»
13 years 7 months ago
Phase Transitions for Greedy Sparse Approximation Algorithms
A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner...
ICASSP
2010
IEEE
13 years 7 months ago
Kronecker product matrices for compressive sensing
Compressive sensing (CS) is an emerging approach for acquisition of signals having a sparse or compressible representation in some basis. While CS literature has mostly focused on...
Marco F. Duarte, Richard G. Baraniuk
JMLR
2012
11 years 10 months ago
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
NETWORKING
2010
13 years 8 months ago
Cost Bounds of Multicast Light-Trees in WDM Networks
The construction of light-trees is one principal subproblem for multicast routing in sparse splitting Wavelength Division Multiplexing (WDM) networks. Due to the light splitting co...
Fen Zhou, Miklós Molnár, Bernard Cou...
ECCV
2010
Springer
14 years 18 days ago
Compressive Acquisition of Dynamic Scenes
Abstract. Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Ny...