Aryan mokhtari (6 risultati)
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 77,05
EUR 2,36 spedizioneSpedito in U.S.A.Quantità: 9 disponibili
Condizione: New.
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 79,49
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 4 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: Usato - Come nuovo
EUR 83,02
EUR 2,36 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 72,21
EUR 17,91 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 10 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 83,83
EUR 17,91 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 9 disponibili
Condizione: As New. Unread book in perfect condition.
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 75,86
EUR 77,63 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 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. …
