Cyrille combettes (10 risultati)
Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics,U.S., US, 2025
- Brossura
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 78,45
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 5 disponibili
Paperback. Condizione: New. 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.
Conditional Gradient Methods
Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Sebastian Pokutta
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 76,11
EUR 2,29 spedizioneSpedito in U.S.A.Quantità: 9 disponibili
Condizione: New.
- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 70,16
EUR 11,70 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 198 pages. 10.00x7.00x0.30 inches. In Stock.
Conditional Gradient Methods
Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Sebastian Pokutta
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 81,32
EUR 2,29 spedizioneSpedito in U.S.A.Quantità: 9 disponibili
Condizione: As New. Unread book in perfect condition.
Conditional Gradient Methods
Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Sebastian Pokutta
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 70,71
EUR 17,54 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 9 disponibili
Condizione: New.
Conditional Gradient Methods: From Core Principles to AI Applications
Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Sebastian Pokutta
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 92,18
EUR 7,60 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 3 disponibili
Condizione: New.
Conditional Gradient Methods
Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Sebastian Pokutta
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 82,06
EUR 17,54 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 9 disponibili
Condizione: As New. Unread book in perfect condition.
Conditional Gradient Methods: From Core Principles to AI Applications
Gábor Braun; Alejandro Carderera; Cyrille W. Combettes; Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Sebastian Pokutta
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 104,01
EUR 3,46 spedizioneSpedito in U.S.A.Quantità: 3 disponibili
Condizione: New.
Conditional Gradient Methods From Core Principles to AI Applications
Gábor Braun|Alejandro Carderera|Cyrille W. Combettes|Hamed Hassani|Amin Karbasi
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2025
- Brossura
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 78,09
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Condizione: New.
Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics,U.S., US, 2025
- Brossura
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 71,36
EUR 76,02 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 5 disponibili
Paperback. Condizione: New. 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.
