Low-Rank Approximation

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This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effecti

Low Rank Approximation

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Data Approximation by Low-complexity Models details the theory, algorithms, and applications of structured low-rank approximation. Efficient local optimization

Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics

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The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied

Handbook of Variational Methods for Nonlinear Geometric Data

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This book covers different, current research directions in the context of variational methods for non-linear geometric data. Each chapter is authored by leading

Applied Machine Learning

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Machine learning methods are now an important tool for scientists, researchers, engineers and students in a wide range of areas. This book is written for people