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024 7 _a10.1007/978-981-15-2910-8
_2doi
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082 0 4 _a006.31
_223
100 1 _aLin, Zhouchen.
_eauthor.
_0(orcid)
_10000-0003-1493-7569
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aAccelerated Optimization for Machine Learning
_h[electronic resource] :
_bFirst-Order Algorithms /
_cby Zhouchen Lin, Huan Li, Cong Fang.
250 _a1st ed. 2020.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2020.
300 _aXXIV, 275 p. 36 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aChapter 1. Introduction -- Chapter 2. Accelerated Algorithms for Unconstrained Convex Optimization -- Chapter 3. Accelerated Algorithms for Constrained Convex Optimization -- Chapter 4. Accelerated Algorithms for Nonconvex Optimization -- Chapter 5. Accelerated Stochastic Algorithms -- Chapter 6. Accelerated Paralleling Algorithms -- Chapter 7. Conclusions.-.
520 _aThis book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
650 0 _aMachine learning.
650 0 _aMathematical optimization.
650 0 _aComputer science
_xMathematics.
650 0 _aMathematics
_xData processing.
650 1 4 _aMachine Learning.
650 2 4 _aOptimization.
650 2 4 _aMathematical Applications in Computer Science.
650 2 4 _aComputational Mathematics and Numerical Analysis.
700 1 _aLi, Huan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aFang, Cong.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811529092
776 0 8 _iPrinted edition:
_z9789811529115
776 0 8 _iPrinted edition:
_z9789811529122
856 4 0 _uhttps://doi.org/10.1007/978-981-15-2910-8
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