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An accessible account of the rich theory surrounding concentration inequalities in probability theory, with applications from machine learning and statistics to high-dimensional geometry. This book introduces key ideas and presents a detailed summary of the state-of-the-art in the area, making it...
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An accessible account of the rich theory surrounding concentration inequalities in probability theory, with applications from machine learning and statistics to high-dimensional geometry. This book introduces key ideas and presents a detailed summary of the state-of-the-art in the area, making it ideal for independent learning and as a reference.
ascunde descrierea
- Editură: Oxford University Press
- Cod:
- Anul publicării: 2016
- Limba: Engleză
- Legarea: Broșată
- Număr de pagini: 496
- Lățimea ambalajului: 23.3 cm
- Înălțimea ambalajului: 15.8 cm
- Adâncimea ambalajului: 3.9 cm
- Greutatea ambalajului: 732 g
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