Conditional Gradient Methods: From Core Principles to AI Applications - Brossura

Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi

 
9781611978551: Conditional Gradient Methods: From Core Principles to AI Applications
Brossura
ISBN 10: 1611978556 ISBN 13: 9781611978551
Casa editrice: Society for Industrial & Applied Mathematics,U.S., 2025

Sinossi

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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Informazioni sugli autori

Sebastian Pokutta is Vice President of the Zuse Institute Berlin (ZIB) and Professor of Mathematics at TU Berlin.

Gábor Braun is currently a member of Zuse Institute Berlin.

Hamed Hassani is an associate professor of the Electrical and Systems Engineering Department, Computer and Information Systems Department, and the Department of Statistics and Data Science at the University of Pennsylvania.

Alejandro Carderera is a Senior Applied Researcher at GitHub, working in Copilot's Applied Science and Models team, focusing on code completions and code review.

Aryan Mokhtari is an Assistant Professor in the Electrical and Computer Engineering Department of the University of Texas at Austin, where he holds the Fellow of Texas Instruments/Kilby.

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Editore
Society for Industrial & Applied Mathematics,U.S.
Data di pubblicazione
2025
Lingua
Inglese
ISBN 10 
1611978556
ISBN 13 
9781611978551
Rilegatura
Copertina flessibile
Numero di pagine
198
Contatto del produttore
non disponibile
Persona responsabile
non disponibile