Cambridge Series in Statistical and Probabilistic Mathematics: High-Dimensional Probability: An Introduction With Applications in Data Science Series Number 47 [Audiobook] download free by Roman Vershynin

Cambridge Series in Statistical and Probabilistic Mathematics: High-Dimensional Probability: An Introduction With Applications in Data Science Series Number 47 Audiobook download free by Roman Vershynin
  • Listen audiobook: Cambridge Series in Statistical and Probabilistic Mathematics: High-Dimensional Probability: An Introduction With Applications in Data Science Series Number 47
  • Author: Roman Vershynin
  • Release date: 2018/10/5
  • Publisher: CAMBRIDGE UNIVERSITY PRESS
  • Language: English
  • Genre or Collection: Computing
  • ISBN: 9781108415194
  • Rating: 9.48 of 10
  • Votes: 618
  • Review by: Corey Mcdade
  • Review rating: 7.45 of 10
  • Review Date: 2018/9/24
  • Duration: 3H48M44S in 256 kbps (59.2 MB)
  • Date of creation of the audiobook: 2018-07-18
  • You can listen to this audiobook in formats: MP3, WAV, AC3, FLAC, AU, MPEG4, WMA (compression ZIP, XZ, RAR, AZW, DMG)
  • Total pages original book: 296
  • Includes a PDF summary of 25 pages
  • Duration of the summary (audio): 19M12S (5 MB)
  • Description or summary of the audiobook: High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate theory, key tools, and modern applications of high-dimensional probability. Concentration inequalities form the core, and it covers both classical results such as Hoeffding's and Chernoff's inequalities and modern developments such as the matrix Bernstein's inequality. It then introduces the powerful methods based on stochastic processes, including such tools as Slepian's, Sudakov's, and Dudley's inequalities, as well as generic chaining and bounds based on VC dimension. A broad range of illustrations is embedded throughout, including classical and modern results for covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, machine learning, compressed sensing, and sparse regression.
  • Other categories, genre or collection: Data Analysis: General, Signal Processing, Probability & Statistics, Pattern Recognition, Econometrics
  • Download servers: 4Shared, Uploaded, Google Drive, Degoo, FreakShare. Compressed in ZIP, XZ, RAR, AZW, DMG
  • Format: Hardback
  • Approximate value: 71.45 USD
  • Dimensions: 183x260x22mm
  • Weight: 710g
  • Printed by: Not Available
  • Published in: Cambridge, United Kingdom

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