On the Lagrangian biduality of sparsity minimization problems
暂无分享,去创建一个
[1] Marc Teboulle,et al. Convex approximations to sparse PCA via Lagrangian duality , 2011, Oper. Res. Lett..
[2] Michael Elad,et al. Image Sequence Denoising via Sparse and Redundant Representations , 2009, IEEE Transactions on Image Processing.
[3] Michael Elad,et al. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[4] Stéphane Chrétien. An alternating l1 approach to the compressed sensing problem , 2007 .
[5] Allen Y. Yang,et al. Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Richard G. Baraniuk,et al. Compressive imaging for video representation and coding , 2006 .
[7] Michael Elad,et al. From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images , 2009, SIAM Rev..
[8] Francis R. Bach,et al. Structured sparsity-inducing norms through submodular functions , 2010, NIPS.
[9] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[10] MaYi,et al. Dense error correction via l1-minimization , 2010 .
[11] Joel A. Tropp,et al. Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.
[12] Sundeep Rangan,et al. Necessary and Sufficient Conditions for Sparsity Pattern Recovery , 2008, IEEE Transactions on Information Theory.
[13] I. Loris. On the performance of algorithms for the minimization of ℓ1-penalized functionals , 2007, 0710.4082.
[14] D. Donoho. For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution , 2006 .
[15] René Vidal,et al. Robust classification using structured sparse representation , 2011, CVPR 2011.
[16] E.J. Candes. Compressive Sampling , 2022 .
[17] Babak Hassibi,et al. On the Reconstruction of Block-Sparse Signals With an Optimal Number of Measurements , 2008, IEEE Transactions on Signal Processing.
[18] John Wright,et al. Dense Error Correction Via $\ell^1$-Minimization , 2010, IEEE Transactions on Information Theory.
[19] Emmanuel J. Candès,et al. Decoding by linear programming , 2005, IEEE Transactions on Information Theory.
[20] E. Candès. The restricted isometry property and its implications for compressed sensing , 2008 .
[21] A. Juditsky,et al. Verifiable Conditions of L1-recovery of Sparse Signals with Sign Restriction , 2009 .
[22] Michael Elad,et al. Sparse Representation for Color Image Restoration , 2008, IEEE Transactions on Image Processing.
[23] David L. Donoho,et al. Neighborly Polytopes And Sparse Solution Of Underdetermined Linear Equations , 2005 .
[24] Yonina C. Eldar,et al. Robust Recovery of Signals From a Structured Union of Subspaces , 2008, IEEE Transactions on Information Theory.
[25] Volkan Cevher,et al. Sparse Signal Recovery Using Markov Random Fields , 2008, NIPS.
[26] A. Martínez,et al. The AR face databasae , 1998 .
[27] Michael Elad,et al. Stable recovery of sparse overcomplete representations in the presence of noise , 2006, IEEE Transactions on Information Theory.
[28] Stéphane Chrétien,et al. An Alternating $l_1$ Approach to the Compressed Sensing Problem , 2008, IEEE Signal Processing Letters.
[29] Aleix M. Martinez,et al. The AR face database , 1998 .