Spectral Methods for Data Science: A Statistical Perspective (Foundations and Trends® in Machine Learning)

Chen, Yuxin/ Chi, Yuejie/ Fan, Jianqing

ISBN 10: 1680838962 / ISBN 13: 9781680838961

Edité par Now Publishers Inc, 2021

A propos de cet article

256 pages. 9.21x6.14x0.54 inches. In Stock.

N° de réf. du vendeur x-1680838962

Détails bibliographiques

• Titre: Spectral Methods for Data Science: A Statistical Perspective (Foundations and Trends® in Machine Learning)
• Éditeur: Now Publishers Inc
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 1680838962
• ISBN à 13 chiffres: 9781680838961
• Reliure: Paperback
• État de l'article: Brand New

A propos de ce titre

Synopsis

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.