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Alternating Direction Method of Multipliers for Machine Learning

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Alternating Direction Method of Multipliers for Machine Learning - Lin, Zhouchen, and Li, Huan, and Fang, Cong
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Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type of optimization problem, and the alternating direction method of multipliers (ADMM) is a commonly used algorithm to solve constrained problems, especially linearly constrained ones. Written by experts in machine learning and optimization, this is the first book providing a state-of-the-art review on ADMM under various scenarios, including deterministic and convex optimization, nonconvex ...

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Alternating Direction Method of Multipliers for Machine Learning 2023, Springer Verlag, Singapore, Singapore

ISBN-13: 9789811698422

Paperback

Alternating Direction Method of Multipliers for Machine Learning 2022, Springer Verlag, Singapore, Singapore

ISBN-13: 9789811698392

Hardcover