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High-Dimensional Probability
Buch von Roman Vershynin
Sprache: Englisch

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Beschreibung
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Über den Autor
Roman Vershynin is Professor of Mathematics at the University of California, Irvine. He studies random geometric structures across mathematics and data sciences, in particular in random matrix theory, geometric functional analysis, convex and discrete geometry, geometric combinatorics, high-dimensional statistics, information theory, machine learning, signal processing, and numerical analysis. His honors include an Alfred Sloan Research Fellowship in 2005, an invited talk at the International Congress of Mathematicians in Hyderabad in 2010, and a Bessel Research Award from the Humboldt Foundation in 2013. His 'Introduction to the Non-Asymptotic Analysis of Random Matrices' has become a popular educational resource for many new researchers in probability and data science.
Inhaltsverzeichnis
Preface; Appetizer: using probability to cover a geometric set; 1. Preliminaries on random variables; 2. Concentration of sums of independent random variables; 3. Random vectors in high dimensions; 4. Random matrices; 5. Concentration without independence; 6. Quadratic forms, symmetrization and contraction; 7. Random processes; 8. Chaining; 9. Deviations of random matrices and geometric consequences; 10. Sparse recovery; 11. Dvoretzky-Milman's theorem; Bibliography; Index.
Details
Erscheinungsjahr: 2019
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
ISBN-13: 9781108415194
ISBN-10: 1108415199
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Vershynin, Roman
Hersteller: Cambridge University Press
Maße: 260 x 183 x 21 mm
Von/Mit: Roman Vershynin
Erscheinungsdatum: 08.03.2019
Gewicht: 0,763 kg
Artikel-ID: 112897063
Über den Autor
Roman Vershynin is Professor of Mathematics at the University of California, Irvine. He studies random geometric structures across mathematics and data sciences, in particular in random matrix theory, geometric functional analysis, convex and discrete geometry, geometric combinatorics, high-dimensional statistics, information theory, machine learning, signal processing, and numerical analysis. His honors include an Alfred Sloan Research Fellowship in 2005, an invited talk at the International Congress of Mathematicians in Hyderabad in 2010, and a Bessel Research Award from the Humboldt Foundation in 2013. His 'Introduction to the Non-Asymptotic Analysis of Random Matrices' has become a popular educational resource for many new researchers in probability and data science.
Inhaltsverzeichnis
Preface; Appetizer: using probability to cover a geometric set; 1. Preliminaries on random variables; 2. Concentration of sums of independent random variables; 3. Random vectors in high dimensions; 4. Random matrices; 5. Concentration without independence; 6. Quadratic forms, symmetrization and contraction; 7. Random processes; 8. Chaining; 9. Deviations of random matrices and geometric consequences; 10. Sparse recovery; 11. Dvoretzky-Milman's theorem; Bibliography; Index.
Details
Erscheinungsjahr: 2019
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
ISBN-13: 9781108415194
ISBN-10: 1108415199
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Vershynin, Roman
Hersteller: Cambridge University Press
Maße: 260 x 183 x 21 mm
Von/Mit: Roman Vershynin
Erscheinungsdatum: 08.03.2019
Gewicht: 0,763 kg
Artikel-ID: 112897063
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