paperback. Zustand: Very Good. No marks or highlighting in the book. Our copy is paperback showing shelf-wear at corner tips and along edges. Heavy book, additional shipping charges to locations outside USA.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New.
Sprache: Englisch
Verlag: Cambridge University Press CUP, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition.
Sprache: Englisch
Verlag: Cambridge University Press, GB, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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EUR 73,53
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In den WarenkorbHardback. Zustand: New. A graduate-level introduction to advanced topics in Markov chain Monte Carlo (MCMC), as applied broadly in the Bayesian computational context. The topics covered have emerged as recently as the last decade and include stochastic gradient MCMC, non-reversible MCMC, continuous time MCMC, and new techniques for convergence assessment. A particular focus is on cutting-edge methods that are scalable with respect to either the amount of data, or the data dimension, motivated by the emerging high-priority application areas in machine learning and AI. Examples are woven throughout the text to demonstrate how scalable Bayesian learning methods can be implemented. This text could form the basis for a course and is sure to be an invaluable resource for researchers in the field.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New.
Sprache: Englisch
Verlag: Cambridge University Press, GB, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: Rarewaves USA, OSWEGO, IL, USA
Hardback. Zustand: New. A graduate-level introduction to advanced topics in Markov chain Monte Carlo (MCMC), as applied broadly in the Bayesian computational context. The topics covered have emerged as recently as the last decade and include stochastic gradient MCMC, non-reversible MCMC, continuous time MCMC, and new techniques for convergence assessment. A particular focus is on cutting-edge methods that are scalable with respect to either the amount of data, or the data dimension, motivated by the emerging high-priority application areas in machine learning and AI. Examples are woven throughout the text to demonstrate how scalable Bayesian learning methods can be implemented. This text could form the basis for a course and is sure to be an invaluable resource for researchers in the field.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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EUR 61,39
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In den Warenkorbhardcover. Zustand: New.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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EUR 66,75
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Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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In den WarenkorbZustand: As New. Unread book in perfect condition.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
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In den WarenkorbHardcover. Zustand: Brand New. 247 pages. 6.00x0.63x9.00 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: UK BOOKS STORE, London, LONDO, Vereinigtes Königreich
EUR 107,63
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In den WarenkorbHardcover. Zustand: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Sprache: Englisch
Verlag: Cambridge University Press, GB, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: Rarewaves USA United, OSWEGO, IL, USA
EUR 77,23
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In den WarenkorbHardback. Zustand: New. A graduate-level introduction to advanced topics in Markov chain Monte Carlo (MCMC), as applied broadly in the Bayesian computational context. The topics covered have emerged as recently as the last decade and include stochastic gradient MCMC, non-reversible MCMC, continuous time MCMC, and new techniques for convergence assessment. A particular focus is on cutting-edge methods that are scalable with respect to either the amount of data, or the data dimension, motivated by the emerging high-priority application areas in machine learning and AI. Examples are woven throughout the text to demonstrate how scalable Bayesian learning methods can be implemented. This text could form the basis for a course and is sure to be an invaluable resource for researchers in the field.
Sprache: Englisch
Verlag: Cambridge University Press, GB, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
EUR 68,70
Anzahl: 1 verfügbar
In den WarenkorbHardback. Zustand: New. A graduate-level introduction to advanced topics in Markov chain Monte Carlo (MCMC), as applied broadly in the Bayesian computational context. The topics covered have emerged as recently as the last decade and include stochastic gradient MCMC, non-reversible MCMC, continuous time MCMC, and new techniques for convergence assessment. A particular focus is on cutting-edge methods that are scalable with respect to either the amount of data, or the data dimension, motivated by the emerging high-priority application areas in machine learning and AI. Examples are woven throughout the text to demonstrate how scalable Bayesian learning methods can be implemented. This text could form the basis for a course and is sure to be an invaluable resource for researchers in the field.
Anbieter: Librairie Victor Sevilla, Paris, Frankreich
Erstausgabe
The Battered Silicon Dispatch Box 1997. In-8 agrafé de 40 pages, au format 21, 5 x 13,5 cm. Couverture illustrée. Plats et intérieur frais. Textes de Chris Redmond avec illustrations en noir de Paul Churchill. Etat proche du neuf. Edition originale à petit tirage.
Anbieter: Librairie Victor Sevilla, Paris, Frankreich
Erstausgabe
The Three Students Plus / Bruce Kennedy 1973. In-8 agrafé de 34 pages, au format 23 x 15,5 cm. Couverture illustrée par J. Jacobson. Plats et intérieur frais. Préface de John Bennett Shaw. Recueil de pastiches et de textes consacrés à Sherlock Holmes par Bruce Kennedy, Susan Dahlinger, Bradley Kjell, Michael Harrison, Thomas Hammond, Douglas Morrison Jr, Chris Redmond, Nicholas Utechin, I.Jopson. Petit tirage imprimé à quelques exemplaires par Bradley Kjell. Etat superbe de fraicheur. Rare édition originale en petit tirage.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 61,55
Anzahl: 1 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 247 pages. 6.00x0.63x9.00 inches. In Stock. This item is printed on demand.
Sprache: Englisch
Verlag: Cambridge University Press, 2025
ISBN 10: 100928844X ISBN 13: 9781009288446
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 83,83
Anzahl: 4 verfügbar
In den WarenkorbZustand: New. Print on Demand.