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Cover: 9781108498029 | High-Dimensional Statistics | Martin J. Wainwright | Buch | Gebunden
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High-Dimensional Statistics
Buch von Martin J. Wainwright
Sprache: Englisch

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Beschreibung
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
Über den Autor
Martin J. Wainwright is a Chancellor's Professor at the University of California, Berkeley, with a joint appointment between the Department of Statistics and the Department of Electrical Engineering and Computer Sciences. His research lies at the nexus of statistics, machine learning, optimization, and information theory, and he has published widely in all of these disciplines. He has written two other books, one on graphical models together with Michael I. Jordan, and one on sparse learning together with Trevor Hastie and Robert Tibshirani. Among other awards, he has received the COPSS Presdients' Award, has been a Medallion Lecturer and Blackwell Lecturer for the Institute of Mathematical Statistics, and has received Best Paper Awards from the Neural Information Processing Systems (NIPS), the International Conference on Machine Learning (ICML), and the Uncertainty in Artificial Intelligence (UAI) conferences, as well as from the Institute of Electrical and Electronics Engineers (IEEE) Information Theory Society.
Inhaltsverzeichnis
1. Introduction; 2. Basic tail and concentration bounds; 3. Concentration of measure; 4. Uniform laws of large numbers; 5. Metric entropy and its uses; 6. Random matrices and covariance estimation; 7. Sparse linear models in high dimensions; 8. Principal component analysis in high dimensions; 9. Decomposability and restricted strong convexity; 10. Matrix estimation with rank constraints; 11. Graphical models for high-dimensional data; 12. Reproducing kernel Hilbert spaces; 13. Nonparametric least squares; 14. Localization and uniform laws; 15. Minimax lower bounds; References; Author index; Subject index.
Details
Erscheinungsjahr: 2019
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108498029
ISBN-10: 1108498027
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Wainwright, Martin J.
Hersteller: Cambridge University Press
Verantwortliche Person für die EU: Produktsicherheitsverantwortliche/r, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 260 x 183 x 35 mm
Von/Mit: Martin J. Wainwright
Erscheinungsdatum: 21.02.2019
Gewicht: 1,257 kg
Artikel-ID: 114087993
Über den Autor
Martin J. Wainwright is a Chancellor's Professor at the University of California, Berkeley, with a joint appointment between the Department of Statistics and the Department of Electrical Engineering and Computer Sciences. His research lies at the nexus of statistics, machine learning, optimization, and information theory, and he has published widely in all of these disciplines. He has written two other books, one on graphical models together with Michael I. Jordan, and one on sparse learning together with Trevor Hastie and Robert Tibshirani. Among other awards, he has received the COPSS Presdients' Award, has been a Medallion Lecturer and Blackwell Lecturer for the Institute of Mathematical Statistics, and has received Best Paper Awards from the Neural Information Processing Systems (NIPS), the International Conference on Machine Learning (ICML), and the Uncertainty in Artificial Intelligence (UAI) conferences, as well as from the Institute of Electrical and Electronics Engineers (IEEE) Information Theory Society.
Inhaltsverzeichnis
1. Introduction; 2. Basic tail and concentration bounds; 3. Concentration of measure; 4. Uniform laws of large numbers; 5. Metric entropy and its uses; 6. Random matrices and covariance estimation; 7. Sparse linear models in high dimensions; 8. Principal component analysis in high dimensions; 9. Decomposability and restricted strong convexity; 10. Matrix estimation with rank constraints; 11. Graphical models for high-dimensional data; 12. Reproducing kernel Hilbert spaces; 13. Nonparametric least squares; 14. Localization and uniform laws; 15. Minimax lower bounds; References; Author index; Subject index.
Details
Erscheinungsjahr: 2019
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108498029
ISBN-10: 1108498027
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Wainwright, Martin J.
Hersteller: Cambridge University Press
Verantwortliche Person für die EU: Produktsicherheitsverantwortliche/r, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 260 x 183 x 35 mm
Von/Mit: Martin J. Wainwright
Erscheinungsdatum: 21.02.2019
Gewicht: 1,257 kg
Artikel-ID: 114087993
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