Csaba szepesvari (42 Ergebnisse)
- Softcover
Anbieter: World of Books (was SecondSale), Montgomery, IL, USAWorld of Books (was SecondSale)
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Befriedigend
EUR 33,91
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
- Softcover
Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 33,93
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Paperback. Zustand: new. Paperback. Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the lea…rner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Softcover
Anbieter: California Books, Miami, FL, USACalifornia Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 37,51
Versand gratisVersand innerhalb von USAAnzahl: Mehr als 20 verfügbar
Zustand: New.
- Softcover
- Erstausgabe
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes KönigreichRarewaves.com USA
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 37,91
Versand gratisVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Paperback. Zustand: New. 1st. Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner a…bout the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration.
- Softcover
Anbieter: Books Puddle, New York, NY, USABooks Puddle
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 35,81
EUR 3,46 VersandVersand innerhalb von USAAnzahl: 1 verfügbar
Zustand: New.
- Softcover
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USARomtrade Corp.
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 42,36
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
- Softcover
Anbieter: Basi6 International, Irving, TX, USABasi6 International
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 42,36
Versand gratisVersand innerhalb von USAAnzahl: 3 verfügbar
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
- Softcover
Anbieter: SMASS Sellers, IRVING, TX, USASMASS Sellers
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 43,84
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Zustand: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 34,68
EUR 13,97 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In English.
Sprache: Englisch
Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2011
- Softcover
Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 56,09
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Paperback. Zustand: new. Paperback. This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together…with the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models. This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Hardcover
Anbieter: California Books, Miami, FL, USACalifornia Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 61,63
Versand gratisVersand innerhalb von USAAnzahl: Mehr als 20 verfügbar
Zustand: New.
Sprache: Englisch
Verlag: Springer-Verlag Berlin and Heidelberg GmbH and Co. KG, DE, 2011
- Softcover
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes KönigreichRarewaves.com USA
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 69,57
Versand gratisVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Paperback. Zustand: New. 2011th. This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together wit…h the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models.
- Hardcover
Anbieter: Books Puddle, New York, NY, USABooks Puddle
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 67,31
EUR 3,46 VersandVersand innerhalb von USAAnzahl: 4 verfügbar
Zustand: New.
Algorithmic Learning Theory: 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011, Proceedings (Lecture Notes in Computer Science)
Jyriki Kivinen, Csaba Szepesv�ri, Esko Ukkonen, Thomas Zeugmann
- Softcover
Anbieter: Chiron Media, Wallingford, Vereinigtes KönigreichChiron Media
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 57,63
EUR 18,07 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 10 verfügbar
Paperback. Zustand: New.
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 61,02
EUR 13,97 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In.
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 62,26
EUR 13,97 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In.
- Hardcover
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes KönigreichRarewaves.com USA
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 77,93
Versand gratisVersand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
Hardback. Zustand: New. Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adve…rsarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.
- Softcover
Anbieter: AussieBookSeller, Truganina, VIC, AustralienAussieBookSeller
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 52,93
EUR 32,08 VersandVersand von Australien nach USAAnzahl: 1 verfügbar
Paperback. Zustand: new. Paperback. Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the lea…rner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 32,09
EUR 61,06 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is th…at only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration.
- Softcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 81,94
EUR 14,58 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 2 verfügbar
Paperback. Zustand: Brand New. 2011 edition. 466 pages. 9.50x6.25x1.00 inches. In Stock.
- Softcover
- Erstausgabe
Anbieter: Rarewaves.com UK, London, Vereinigtes KönigreichRarewaves.com UK
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 34,58
EUR 75,81 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Paperback. Zustand: New. 1st.
- Hardcover
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USARomtrade Corp.
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 116,63
Versand gratisVersand innerhalb von USAAnzahl: 5 verfügbar
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
- Hardcover
Anbieter: moluna, Greven, Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 64,81
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Zustand: New. Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for gra.
Algorithmic learning theory 22nd international conference ; proceedings.
Kivinen, Jyrki , Csaba Szepesvári and Esko Zeugmann Thomas [Hrsg.] Ukkonen:
- Softcover
Anbieter: BBB-Internetbuchantiquariat, Bremen, DeutschlandBBB-Internetbuchantiquariat
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Sehr gut
EUR 39,30
EUR 79,00 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Softcover/Paperback. Zustand: Sehr gut. 451 Seiten Zustand: sehr gut; Ungelesen; Fußschnitt leicht angeschmutzt; T-AA1357 9783642244117 Wenn das Buch einen Schutzumschlag hat, ist das ausdrücklich erwähnt. Rechnung mit ausgewiesener Mwst. Sprache: Englisch Gewicht in Gramm: 745.
- Hardcover
Anbieter: SMASS Sellers, IRVING, TX, USASMASS Sellers
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 122,29
Versand gratisVersand innerhalb von USAAnzahl: 5 verfügbar
Zustand: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Sprache: Englisch
Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2011
- Softcover
Anbieter: AussieBookSeller, Truganina, VIC, AustralienAussieBookSeller
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 92,81
EUR 32,08 VersandVersand von Australien nach USAAnzahl: 1 verfügbar
Paperback. Zustand: new. Paperback. This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together…with the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models. This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 68,24
EUR 65,14 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Neuware.
Algorithmic Learning Theory: 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011, Proceedings: 6925 (Lecture Notes in Computer Science, 6925)
Jyriki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann
- Softcover
Anbieter: Rarewaves.com UK, London, Vereinigtes KönigreichRarewaves.com UK
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 64,65
EUR 75,81 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Paperback. Zustand: New. 2011th.
- Hardcover
Anbieter: Rarewaves.com UK, London, Vereinigtes KönigreichRarewaves.com UK
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 72,59
EUR 75,81 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
Hardback. Zustand: New. Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adve…rsarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.
- Softcover
Anbieter: Buchpark, Trebbin, DeutschlandBuchpark
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Sehr gut
EUR 43,93
EUR 105,00 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 451 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
