Conditional Gradient Methods: From Core Principles to AI Applications offers a definitive and modern treatment of one of the most elegant and versatile algorithmic families in optimization: the Frank-Wolfe method and its many variants. Originally proposed in the 1950s, these projection-free techniques have seen a powerful resurgence, now playing a central role in machine learning, signal processing, and large-scale data science. This comprehensive monograph unites deep theoretical insights with practical considerations, ...
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Conditional Gradient Methods: From Core Principles to AI Applications offers a definitive and modern treatment of one of the most elegant and versatile algorithmic families in optimization: the Frank-Wolfe method and its many variants. Originally proposed in the 1950s, these projection-free techniques have seen a powerful resurgence, now playing a central role in machine learning, signal processing, and large-scale data science. This comprehensive monograph unites deep theoretical insights with practical considerations, guiding readers through the foundations of constrained optimization and into cutting-edge territory, including stochastic, online, and distributed settings. With a clear narrative, rigorous proofs, and illuminating illustrations, the book demystifies adaptive variants, away-steps, and the nuances of dealing with structured convex sets. A FrankWolfe.jl Julia package that implements most of the algorithms in the book is available on a supplementary website.
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Add this copy of Conditional Gradient Methods: From Core Principles to to cart. $101.41, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2025 by Society for Industrial & Applied Mathematics,U.S..
Edition:
2025, Society for Industrial & Applied Mathematics,U.S.
Publisher:
Society for Industrial & Applied Mathematics,U.S.
Published:
2025
Language:
English
Alibris ID:
18949144755
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Fine. Intended for professional and scholarly audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Conditional Gradient Methods: From Core Principles to to cart. $102.43, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2025 by Society for Industrial & Applied Mathematics,U.S..
Edition:
2025, Society for Industrial & Applied Mathematics,U.S.
Publisher:
Society for Industrial & Applied Mathematics,U.S.
Published:
2025
Language:
English
Alibris ID:
18948897243
Shipping Options:
Standard Shipping: $4.99
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Intended for professional and scholarly audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Conditional Gradient Methods: From Core Principles to to cart. $102.44, new condition, Sold by Booksplease rated 4.0 out of 5 stars, ships from Southport, MERSEYSIDE, UNITED KINGDOM, published 2025 by Society for Industrial & Applied Mathematics,U.S..
Edition:
2025, Society for Industrial & Applied Mathematics,U.S.
