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.
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 256. N° de réf. du vendeur 26390201320
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 256. N° de réf. du vendeur 389431351
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 256. N° de réf. du vendeur 18390201314
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