lugosi gabor (18 Ergebnisse)

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Brand New. reprint edition. 496 pages. 8.43x5.85x0.73 inches. In Stock.

hardcover. Zustand: Very Good.

Paperback. Zustand: Brand New. 1st edition. 399 pages. 9.29x6.06x0.87 inches. In Stock.

24 x 16. 167 Seiten. Abbildungen. OKart. Sehr guter Zustand. hu Gewicht in Gramm: 400.

Paperback. Zustand: Brand New. reprint edition. 496 pages. 8.43x5.85x0.73 inches. In Stock.

Zustand: Fair. Condition: Fair | Pages: 496 | Language: English | Product Type: Books.

Zustand: New. pp. xii + 394 Illus.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 20th International Conference on Algorithmic Learning Theory, ALT 2009, held in Porto, Portugal, in October 2009, co-located with the 12th International Conference on Discovery Science, DS 2009. The 26 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 60 submissions. The papers are divided into topical sections of papers on online learning, learning graphs, active learning and query learning, statistical learning, inductive inference, and semisupervised and unsupervised learning. The volume also contains abstracts of the invited talks: Sanjoy Dasgupta, The Two Faces of Active Learning; Hector Geffner, Inference and Learning in Planning; Jiawei Han, Mining Heterogeneous; Information Networks By Exploring the Power of Links, Yishay Mansour, Learning and Domain Adaptation; Fernando C.N. Pereira, Learning on the Web.

Taschenbuch. Zustand: Neu. Algorithmic Learning Theory | 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009, Proceedings | Ricard Gavaldà (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | Springer-Verlag GmbH | EAN 9783642044137 | Verantwortliche Person für die EU: Lauinger, Sonia, Sonia Lauinger, Lauinger Verlag, Heinrich-Köhler-Platz 8, 76187 Karlsruhe, mail[at]lauinger-verlag[dot]de | Anbieter: preigu.

Zustand: New. pp. 660 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Hardcover. Zustand: Brand New. new title edition. 406 pages. 10.00x7.00x1.00 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Taschenbuch. Zustand: Neu. Learning Theory | 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, Proceedings | Gábor Lugosi (u. a.) | Taschenbuch | xii | Englisch | 2006 | Springer | EAN 9783540352945 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA, June 2006. The book presents 43 revised full papers together with 2 articles on open problems and 3 invited lectures. The papers cover a wide range of topics including clustering, un- and semi-supervised learning, statistical learning theory, regularized learning and kernel methods, query learning and teaching, inductive inference, and more.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This text explores a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric. It is the first book on this topic. The text is intended for first-year graduate students in statistics and learning theory, and offers a host of opportunities for further research and thesis topics. Each chapter corresponds roughly to one lecture, and is supplemented with many classroom exercises. A one year course in probability theory at the level of Feller's Volume 1 should be more than adequate preparation. Gabor Lugosi is Professor at Universitat Pompeu Fabra in Barcelona, and Luc Debroye is Professor at McGill University in Montreal. In 1996, the authors, together with Lászlo Györfi, published the successful text, A Probabilistic Theory of Pattern Recognition with Springer-Verlag. Both authors have made many contributions in the area of nonparametric estimation.

Taschenbuch. Zustand: Neu. Combinatorial Methods in Density Estimation | Gabor Lugosi (u. a.) | Taschenbuch | xii | Englisch | 2012 | Springer US | EAN 9781461265276 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This text explores a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric. It is the first book on this topic. The text is intended for first-year graduate students in statistics and learning theory, and offers a host of opportunities for further research and thesis topics. Each chapter corresponds roughly to one lecture, and is supplemented with many classroom exercises. A one year course in probability theory at the level of Feller's Volume 1 should be more than adequate preparation. Gabor Lugosi is Professor at Universitat Pompeu Fabra in Barcelona, and Luc Debroye is Professor at McGill University in Montreal. In 1996, the authors, together with Lászlo Györfi, published the successful text, A Probabilistic Theory of Pattern Recognition with Springer-Verlag. Both authors have made many contributions in the area of nonparametric estimation.