Algorithmic High-Dimensional Robust Statistics (Hardcover)
Language: English
Published by Cambridge University Press, Cambridge, 2023
- Hardcover
- New
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
£ 67.49
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Hardcover. Robust statistics is the study of designing estimators that perform well even when the dataset significantly deviates from the idealized modeling assumptions, such as in the presence of model misspecification or adversarial outliers in the dataset. The classical statistical theory, dating back to pioneering works by Tukey and Huber, characterizes the information-theoretic limits of robust estimation for most common problems. A recent line of work in computer science gave the first computationally efficient robust estimators in high dimensions for a range of learning tasks. This reference text for graduate students, researchers, and professionals in machine learning theory, provides an overview of recent developments in algorithmic high-dimensional robust statistics, presenting the underlying ideas in a clear and unified manner, while leveraging new perspectives on the developed techniques to provide streamlined proofs of these results. The most basic and illustrative results are analyzed in each chapter, while more tangential developments are explored in the exercises. 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 item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9781108837811
- Title
- Algorithmic High-Dimensional Robust Statistics (Hardcover)
- Author
- Ilias Diakonikolas
- Publisher
- Cambridge University Press, Cambridge
- Publication year
- 2023
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1108837816
- ISBN 13
- 9781108837811
"Synopsis" may belong to another edition of this title.
About the Author
Daniel M. Kane is an associate professor at the University of California, San Diego in the departments of Computer Science and Mathematics. He is a four-time Putnam Fellow and two-time IMO gold medallist. Kane's research interests include number theory, combinatorics, computational complexity, and computational statistics.
"About the title" may belong to another edition of this title.
CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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