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Cover: 9781108837811 | Algorithmic High-Dimensional Robust Statistics | Diakonikolas (u. a.)
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Algorithmic High-Dimensional Robust Statistics
Buch von Ilias Diakonikolas (u. a.)
Sprache: Englisch

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Beschreibung
This reference text offers a clear unified treatment for graduate students, academic researchers, and professionals interested in understanding and developing statistical procedures for high-dimensional data that are robust to idealized modeling assumptions, including robustness to model misspecification and to adversarial outliers in the dataset.
This reference text offers a clear unified treatment for graduate students, academic researchers, and professionals interested in understanding and developing statistical procedures for high-dimensional data that are robust to idealized modeling assumptions, including robustness to model misspecification and to adversarial outliers in the dataset.
Über den Autor
Ilias Diakonikolas is an associate professor of computer science at the University of Wisconsin-Madison. His current research focuses on the algorithmic foundations of machine learning. Diakonikolas is a recipient of a number of research awards, including the best paper award at NeurIPS 2019.
Inhaltsverzeichnis
1. Introduction to robust statistics; 2. Efficient high-dimensional robust mean estimation; 3. Algorithmic refinements in robust mean estimation; 4. Robust covariance estimation; 5. List-decodable learning; 6. Robust estimation via higher moments; 7. Robust supervised learning; 8. Information-computation tradeoffs in high-dimensional robust statistics; A. Mathematical background; References; Index.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
ISBN-13: 9781108837811
ISBN-10: 1108837816
Sprache: Englisch
Einband: Gebunden
Autor: Diakonikolas, Ilias
Kane, Daniel M
Hersteller: Cambridge University Press
Maße: 235 x 163 x 22 mm
Von/Mit: Ilias Diakonikolas (u. a.)
Erscheinungsdatum: 07.09.2023
Gewicht: 0,559 kg
Artikel-ID: 126828288
Über den Autor
Ilias Diakonikolas is an associate professor of computer science at the University of Wisconsin-Madison. His current research focuses on the algorithmic foundations of machine learning. Diakonikolas is a recipient of a number of research awards, including the best paper award at NeurIPS 2019.
Inhaltsverzeichnis
1. Introduction to robust statistics; 2. Efficient high-dimensional robust mean estimation; 3. Algorithmic refinements in robust mean estimation; 4. Robust covariance estimation; 5. List-decodable learning; 6. Robust estimation via higher moments; 7. Robust supervised learning; 8. Information-computation tradeoffs in high-dimensional robust statistics; A. Mathematical background; References; Index.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
ISBN-13: 9781108837811
ISBN-10: 1108837816
Sprache: Englisch
Einband: Gebunden
Autor: Diakonikolas, Ilias
Kane, Daniel M
Hersteller: Cambridge University Press
Maße: 235 x 163 x 22 mm
Von/Mit: Ilias Diakonikolas (u. a.)
Erscheinungsdatum: 07.09.2023
Gewicht: 0,559 kg
Artikel-ID: 126828288
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