Graph-Based Semi-Supervised Learning

Language: English

Published by Springer, Springer Aug 2014, 2014

3031004434 / 9783031004438

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This item is printed on demand - Print on Demand Titel. Neuware -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 / IndexSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.

Seller Inventory # 9783031004438

Title
Graph-Based Semi-Supervised Learning
Author
Amarnag Subramanya
Publisher
Springer, Springer Aug 2014
Publication year
2014
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3031004434
ISBN 13
9783031004438
Item weight
255 grams
Dimensions
235x191x8 mm

buchversandmimpf2000

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