Verfasst von:	Wright, Stephen J. [VerfasserIn]
	Recht, Benjamin [VerfasserIn]
Titel:	Optimization for data analysis
Verf.angabe:	Stephen J. Wright (University of Wisconsin-Madison), Benjamin Recht (University of California, Berkeley)
Verlagsort:	Cambridge, United Kingdom ; New York, NY, USA ; Port Melbourne, VIC, Australia ; New Delhi, India ; Singapore
Verlag:	Cambridge University Press
Jahr:	2022
Umfang:	x, 227 Seiten
Illustrationen:	Illustrationen
Fussnoten:	Includes bibliographical references and index
ISBN:	978-1-316-51898-4
Abstract:	"Optimization formulations and algorithms have long played a central role in data analysis and machine learning. Maximum likelihood concepts date to Gauss and Laplace in the late 1700s ; problems of this type drove developments in unconstrained optimization in the latter half of the 20th century. Mangasarian's papers in the 1960s on pattern separation using linear programming made an explicit connection between machine learning and optimization in the early days of the former subject. During the 1990s, optimization techniques (especially quadratic programming and duality) were key to the development of support vector machines and kernel learning. The period 1997-2010 saw many synergies emerge between regularized / sparse optimization, variable selection, and compressed sensing. In the current era of deep learning, two optimization techniques-stochastic gradient and automatic differentiation (a.k.a. back-propagation)-are essential"--
DOI:	doi:10.1017/9781009004282
URL:	Inhaltsverzeichnis: https://www.gbv.de/dms/ilmenau/toc/1767772270.PDF
	https://zbmath.org/?q=an%3A7364940
	DOI: https://doi.org/10.1017/9781009004282
	DOI: https://doi.org/10.1017/9781009004282
Schlagwörter:	(s)Datenanalyse    / (s)Big Data    / (s)Optimierung
Sprache:	eng
Bibliogr. Hinweis:	Erscheint auch als : Online-Ausgabe: Wright, Stephen J., 1960 - : Optimization for data analysis. - Cambridge : Cambridge University Press, 2022. - 1 online resource (x, 227 pages)
RVK-Notation:	SK 870
Sach-SW:	MATHEMATICS / General
K10plus-PPN:	1767772270