Sohail Bahmani's Algorithms for Sparsity-Constrained Optimization PDF

By Sohail Bahmani

ISBN-10: 3319018809

ISBN-13: 9783319018805

ISBN-10: 3319018817

ISBN-13: 9783319018812

This thesis demonstrates thoughts that offer quicker and extra actual ideas to quite a few difficulties in computer studying and sign processing. the writer proposes a "greedy" set of rules, deriving sparse options with promises of optimality. using this set of rules eliminates a few of the inaccuracies that happened with using prior models.

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The Annals of Statistics, 36(2):614–645, 2008. V. Vapnik. Statistical Learning Theory. Wiley, New York, NY, 1998. ISBN 978-0-471-03003-4. T. Zhang. Sparse recovery with orthogonal matching pursuit under RIP. IEEE Transactions on Information Theory, 57(9):6215–6221, Sept. 2011. 1 Background Quantization is an indispensable part of digital signal processing and digital communications systems. To incorporate CS methods in these systems, it is thus necessary to analyze and evaluate them considering the effect of measurement quantization.

A. Tropp. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples. Applied and Computational Harmonic Analysis, 26(3):301–321, 2009. Y. C. Pati, R. Rezaiifar, and P. S. Krishnaprasad. Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition. In Conference Record of the 27th Asilomar Conference on Signals, Systems and Computers, volume 1, pages 40–44, Pacific Grove, CA, Nov. 1993. Y. Shechtman, Y. C. Eldar, A. Szameit, and M. Segev.

Lauderdale, FL, USA, 2011. JMLR W&CP. D. Needell and J. A. Tropp. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples. Applied and Computational Harmonic Analysis, 26(3):301–321, 2009. S. Negahban, P. Ravikumar, M. Wainwright, and B. Yu. A unified framework for highdimensional analysis of M -estimators with decomposable regularizers. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems, volume 22, pages 1348–1356.

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Algorithms for Sparsity-Constrained Optimization by Sohail Bahmani

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