Language: English
Published by Morgan and Claypool Publishers, 2010
ISBN 10: 1598296299 ISBN 13: 9781598296297
Seller: suffolkbooks, Center moriches, NY, U.S.A.
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Soft Cover. Condition: Good. Ex-library with the usual features. Library label on front cover. The interior is clean and tight. Binding is good. Cover shows light wear. Ex-Library.
Published by AVRDC the World Vegetable Center, Taiwan, 2003
Seller: Eastburn Books, Albany, OR, U.S.A.
Soft cover. Condition: Very Good. No Jacket. VG Green and white wraps with green title and illustration. Clean and solidly stapled. Checkmark to top forward corner of cover, otherwise unmarked. Mild bending to corners. 26 pp., charts and graphs. Recent publication from this respected research organization. 4to - over 9¾" - 12" tall. Book.
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Paperback. Condition: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. Except for library markings, text block clean and unmarked. Tight binding.
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Language: English
Published by Springer International Publishing AG, CH, 2016
ISBN 10: 3031012224 ISBN 13: 9783031012228
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Paperback. Condition: New. Over the last decade, differential privacy (DP) has emerged as the de facto standard privacy notion for research in privacy-preserving data analysis and publishing. The DP notion offers strong privacy guarantee and has been applied to many data analysis tasks.This Synthesis Lecture is the first of two volumes on differential privacy. This lecture differs from the existing books and surveys on differential privacy in that we take an approach balancing theory and practice. We focus on empirical accuracy performances of algorithms rather than asymptotic accuracy guarantees. At the same time, we try to explain why these algorithms have those empirical accuracy performances. We also take a balanced approach regarding the semantic meanings of differential privacy, explaining both its strong guarantees and its limitations.We start by inspecting the definition and basic properties of DP, and the main primitives for achieving DP. Then, we give a detailed discussion on the the semantic privacy guarantee provided by DP and the caveats when applying DP. Next, we review the state of the art mechanisms for publishing histograms for low-dimensional datasets, mechanisms for conducting machine learning tasks such as classification, regression, and clustering, and mechanisms for publishing information to answer marginal queries for high-dimensional datasets. Finally, we explain the sparse vector technique, including the many errors that have been made in the literature using it.The planned Volume 2 will cover usage of DP in other settings, including high-dimensional datasets, graph datasets, local setting, location privacy, and so on. We will also discuss various relaxations of DP.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st edition NO-PA16APR2015-KAP.
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Language: English
Published by Springer-Nature New York Inc, 2020
ISBN 10: 3030589501 ISBN 13: 9783030589509
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 788 pages. 9.25x6.10x2.99 inches. In Stock.
Language: English
Published by Springer-Nature New York Inc, 2020
ISBN 10: 3030590127 ISBN 13: 9783030590123
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 788 pages. 9.25x6.10x2.83 inches. In Stock.