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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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High-Dimensional Data Analysis with Low-Dimensional Models - Principles, Computation, and Applications (Hardcover)
Loot Price: R1,994
Discovery Miles 19 940
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High-Dimensional Data Analysis with Low-Dimensional Models - Principles, Computation, and Applications (Hardcover)
Expected to ship within 10 - 15 working days
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Connecting theory with practice, this systematic and rigorous
introduction covers the fundamental principles, algorithms and
applications of key mathematical models for high-dimensional data
analysis. Comprehensive in its approach, it provides unified
coverage of many different low-dimensional models and analytical
techniques, including sparse and low-rank models, and both convex
and non-convex formulations. Readers will learn how to develop
efficient and scalable algorithms for solving real-world problems,
supported by numerous examples and exercises throughout, and how to
use the computational tools learnt in several application contexts.
Applications presented include scientific imaging, communication,
face recognition, 3D vision, and deep networks for classification.
With code available online, this is an ideal textbook for senior
and graduate students in computer science, data science, and
electrical engineering, as well as for those taking courses on
sparsity, low-dimensional structures, and high-dimensional data.
Foreword by Emmanuel Candes.
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