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001 978-3-319-01881-2
003 DE-He213
005 20140220082510.0
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008 131007s2014 gw | s |||| 0|eng d
020 _a9783319018812
_9978-3-319-01881-2
024 7 _a10.1007/978-3-319-01881-2
_2doi
050 4 _aTK5102.9
050 4 _aTA1637-1638
050 4 _aTK7882.S65
072 7 _aTTBM
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC008000
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072 7 _aCOM073000
_2bisacsh
082 0 4 _a621.382
_223
100 1 _aBahmani, Sohail.
_eauthor.
245 1 0 _aAlgorithms for Sparsity-Constrained Optimization
_h[electronic resource] /
_cby Sohail Bahmani.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXI, 107 p. 13 illus., 12 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053 ;
_v261
505 0 _aIntroduction -- Preliminaries -- Sparsity-Constrained Optimization -- Background -- 1-bit Compressed Sensing -- Estimation Under Model-Based Sparsity -- Projected Gradient Descent for `p-constrained Least Squares -- Conclusion and Future Work.
520 _aThis thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a"greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.
650 0 _aEngineering.
650 0 _aComputer vision.
650 1 4 _aEngineering.
650 2 4 _aSignal, Image and Speech Processing.
650 2 4 _aMathematical Applications in Computer Science.
650 2 4 _aImage Processing and Computer Vision.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319018805
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053 ;
_v261
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-01881-2
912 _aZDB-2-ENG
999 _c92764
_d92764