000			02055nam a2200289Ia 4500
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008			220909b |||||||| |||| 00| 0 eng d
020			_a9781439828694
037			_cTextbook
040			_aCSL _beng _cCSL
041			_aeng
084			_aD65,8(B):(B288) Q5 TD _qCSL
100			_aRish, Irina _eauthor _9816483
245		0	_aSparse modeling _b: Theory, algorithms, and applications
260			_aBoca Raton : _bCRC Press, _c2015.
300			_axviii, 231p. _b: ill.
500			_aEpilogue 185-186p.; Appendix 187-202p.; Bibliography 203-226p.; Index 227-231p.
520			_aSparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing. Sparse Modeling: Theory, Algorithms, and Applications provides an introduction to the growing field of sparse modeling, including application examples, problem formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery. The book gets you up to speed on the latest sparsity-related developments and will motivate you to continue learning about the field. The authors first present motivating examples and a high-level survey of key recent developments in sparse modeling. The book then describes optimization problems involving commonly used sparsity-enforcing tools, presents essential theoretical results, and discusses several state-of-the-art algorithms for finding sparse solutions.
650			_a Beyond LASSO _9816484
650			_a Sparse graphical models _9816485
650			_a Theoretical results _9816486
650			_aSparse recovery _9816487
700			_aGrabarnik, Genady Ya _eco-author _9816488
942			_hD65,8(B):(B288) Q5 TD _cTB _2CC _n0
999			_c6551 _d6551