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Anglický jazyk
Spectral Methods for Data Science
Autor: Yuxin Chen
In contemporary science and engineering applications, the volume of available data is growing at an enormous rate. Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete... Viac o knihe
Na objednávku
107.55 €
bežná cena: 119.50 €
O knihe
In contemporary science and engineering applications, the volume of available data is growing at an enormous rate. Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. A diverse array of applications have been found in machine learning, imaging science, financial and econometric modeling, and signal processing.
This monograph presents a systematic, yet accessible introduction to spectral methods from a modern statistical perspective, highlighting their algorithmic implications in diverse large-scale applications. The authors provide a unified and comprehensive treatment that establishes the theoretical underpinnings for spectral methods, particularly through a statistical lens.
Building on years of research experience in the field, the authors present a powerful framework, called leave-one-out analysis, that proves effective and versatile for delivering fine-grained performance guarantees for a variety of problems. This book is essential reading for all students, researchers and practitioners working in Data Science.
- Vydavateľstvo: Now Publishers Inc
- Rok vydania: 2021
- Formát: Paperback
- Rozmer: 234 x 156 mm
- Jazyk: Anglický jazyk
- ISBN: 9781680838961
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