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Ajouter au panierhardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Ajouter au panierHardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.27.
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Ajouter au panierpaperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Ajouter au panierEtat : Very Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: Reprint ] Publisher: The MIT Press Pub Date: 9/22/2006 Binding: Hardcover Pages: 528 Reprint edition.
Edité par Springer International Publishing AG, CH, 2014
ISBN 10 : 3031004434 ISBN 13 : 9783031004438
Langue: anglais
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
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Ajouter au panierPaperback. Etat : New. 1°. While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL algorithms, which bring together these two lines of work, have been shown to outperform the state-of-the-art in many applications in speech processing, computer vision, natural language processing, and other areas of Artificial Intelligence. Recognizing this promising and emerging area of research, this synthesis lecture focuses on graph-based SSL algorithms (e.g., label propagation methods). Our hope is that after reading this book, the reader will walk away with the following: (1) an in-depth knowledge of the current state-of-the-art in graph-based SSL algorithms, and the ability to implement them; (2) the ability to decide on the suitability of graph-based SSL methods for a problem; and (3) familiarity with different applications where graph-based SSL methods have been successfully applied. Table of Contents: Introduction / Graph Construction / Learning and Inference / Scalability / Applications / Future Work / Bibliography / Authors' Biographies / Index.
Edité par Springer International Publishing AG, 2009
ISBN 10 : 3031004205 ISBN 13 : 9783031004209
Langue: anglais
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Ajouter au panierEtat : New. 1st edition NO-PA16APR2015-KAP.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Ajouter au panierEtat : New. In English.
Edité par Springer International Publishing AG, 2009
ISBN 10 : 3031004205 ISBN 13 : 9783031004209
Langue: anglais
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Ajouter au panierHardcover. Etat : Fine. Etat de la jaquette : Very Good. Fine, minute shelf wear to dust jacket, pages bright and smooth, all around a nice tight used copy.
Edité par Springer International Publishing AG, CH, 2009
ISBN 10 : 3031004205 ISBN 13 : 9783031004209
Langue: anglais
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Edition originale
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Ajouter au panierPaperback. Etat : New. 1st. Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data are unlabeled, or in the supervised paradigm (e.g., classification, regression) where all the data are labeled. The goal of semi-supervised learning is to understand how combining labeled and unlabeled data may change the learning behavior, and design algorithms that take advantage of such a combination. Semi-supervised learning is of great interest in machine learning and data mining because it can use readily available unlabeled data to improve supervised learning tasks when the labeled data are scarce or expensive. Semi-supervised learning also shows potential as a quantitative tool to understand human category learning, where most of the input is self-evidently unlabeled. In this introductory book, we present some popular semi-supervised learning models, including self-training, mixture models, co-training and multiview learning, graph-based methods, and semi-supervised support vector machines. For each model, we discuss its basic mathematical formulation. The success of semi-supervised learning depends critically on some underlying assumptions. We emphasize the assumptions made by each model and give counterexamples when appropriate to demonstrate the limitations of the different models. In addition, we discuss semi-supervised learning for cognitive psychology. Finally, we give a computational learning theoretic perspective on semi-supervised learning, and we conclude the book with a brief discussion of open questions in the field. Table of Contents: Introduction to Statistical Machine Learning / Overview of Semi-Supervised Learning / Mixture Models and EM / Co-Training / Graph-Based Semi-Supervised Learning / Semi-Supervised Support Vector Machines/ Human Semi-Supervised Learning / Theory and Outlook.
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Ajouter au panierEtat : New. In English.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Edité par LAP LAMBERT Academic Publishing, 2010
ISBN 10 : 3843379106 ISBN 13 : 9783843379106
Langue: anglais
Vendeur : Zubal-Books, Since 1961, Cleveland, OH, Etats-Unis
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Ajouter au panierEtat : New. 132 pp., paperback, new. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 37,66
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Ajouter au panierEtat : New. In English.
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Ajouter au panierEtat : New. 1st edition NO-PA16APR2015-KAP.
Vendeur : Chiron Media, Wallingford, Royaume-Uni
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Ajouter au panierPaperback. Etat : New.
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierPF. Etat : New.