Da: HPB-Red, Dallas, TX, U.S.A.
hardcover. Condizione: 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!
Hardcover. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.27.
Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Da: HPB-Red, Dallas, TX, U.S.A.
paperback. Condizione: 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!
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Condizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Condizione: As New. Unread book in perfect condition.
EUR 30,98
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Condizione: New.
Condizione: As New. Unread book in perfect condition.
Condizione: New.
Condizione: New.
Da: BookHolders, Towson, MD, U.S.A.
Condizione: 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.
Editore: Springer International Publishing AG, 2009
ISBN 10: 3031004205 ISBN 13: 9783031004209
Lingua: Inglese
Da: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Editore: Springer International Publishing AG, CH, 2014
ISBN 10: 3031004434 ISBN 13: 9783031004438
Lingua: Inglese
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 43,00
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: 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.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 30,23
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Aggiungi al carrelloCondizione: New. In English.
Editore: Springer International Publishing AG, 2009
ISBN 10: 3031004205 ISBN 13: 9783031004209
Lingua: Inglese
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 39,51
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Hardcover. Condizione: Fine. Condizione sovraccoperta: Very Good. Fine, minute shelf wear to dust jacket, pages bright and smooth, all around a nice tight used copy.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 33,45
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Aggiungi al carrelloCondizione: New. In English.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 30,22
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Aggiungi al carrelloCondizione: New.
Editore: Springer International Publishing AG, CH, 2009
ISBN 10: 3031004205 ISBN 13: 9783031004209
Lingua: Inglese
Da: Rarewaves.com USA, London, LONDO, Regno Unito
Prima edizione
EUR 48,28
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Aggiungi al carrelloPaperback. Condizione: 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.
EUR 30,97
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Aggiungi al carrelloCondizione: New.
Editore: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843379106 ISBN 13: 9783843379106
Lingua: Inglese
Da: Zubal-Books, Since 1961, Cleveland, OH, U.S.A.
Condizione: 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.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 37,54
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In English.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Da: Chiron Media, Wallingford, Regno Unito
EUR 33,79
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
EUR 35,08
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 35,40
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.