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Amini, Massih-Reza; Usunier, Nicolas - Learning with Partially Labeled and Interdependent Data - 9783319353906 - V9783319353906
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Learning with Partially Labeled and Interdependent Data

€ 73.60
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Description for Learning with Partially Labeled and Interdependent Data Paperback. Num Pages: 119 pages, 12 black & white illustrations, biography. BIC Classification: PBT; UNF; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 7. Weight in Grams: 197.

This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data. It reveals new applications, primarily web related, that transgress the classical machine learning framework through learning with interdependent data.

The book traces how the semi-supervised paradigm and the learning to rank paradigm emerged from new web applications, leading to a massive production of heterogeneous textual data. It explains how semi-supervised learning techniques are widely used, but only allow a limited analysis of the information content and thus do not meet the demands of many web-related tasks.

Later chapters deal with the development of learning methods ... Read more

Researchers and professionals in machine learning will find these new perspectives and solutions valuable. Learning with Partially Labeled and Interdependent Data is also useful for advanced-level students of computer science, particularly those focused on statistics and learning.

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Product Details

Format
Paperback
Publication date
2016
Publisher
Springer International Publishing AG Switzerland
Number of pages
119
Condition
New
Number of Pages
106
Place of Publication
Cham, Switzerland
ISBN
9783319353906
SKU
V9783319353906
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

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