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Differential Privacy Dynamic Data by Jerome (23 results)
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Condition: New.
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Differential Privacy for Dynamic Data
Published by Springer Nature Switzerland AG, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Differential Privacy for Dynamic Data
Published by Springer Nature Switzerland AG, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Differential Privacy for Dynamic Data (SpringerBriefs in Control, Automation and Robotics)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 51.12
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Differential Privacy for Dynamic Data
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Differential Privacy for Dynamic Data
Published by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. 2020 ed. This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.
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Differential Privacy For Dynamic Data
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Differential Privacy for Dynamic Data
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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PF. Condition: New.
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Condition: New. pp. 110.
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Condition: New.
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Condition: NEW.
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Paperback. Condition: Brand New. 124 pages. 9.25x6.10x0.39 inches. In Stock.
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Differential Privacy for Dynamic Data
Published by Springer International Publishing, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Condition: New. Introduces readers to the emerging topic of privacy in the context of signal processing and control systems Illustrates concepts, with case studies that analyze real-world public datasetsProvides a syst.
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Differential Privacy for Dynamic Data
Published by Springer International Publishing, Springer International Publishing Mär 2020, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 124 pp. Englisch.
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Differential Privacy for Dynamic Data
Published by Springer International Publishing, Springer International Publishing, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing.For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.
-
Differential Privacy for Dynamic Data
Published by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Paperback. Condition: New. 2020 ed. This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.
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Paperback. Condition: Brand New. 124 pages. 9.25x6.10x0.39 inches. In Stock. This item is printed on demand.
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Differential Privacy for Dynamic Data
Published by Springer International Publishing Mrz 2020, 2020
ISBN 10: 3030410382 ISBN 13: 9783030410384
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing.For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks. 124 pp. Englisch.
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Condition: New. Print on Demand pp. 110.
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Condition: New. PRINT ON DEMAND pp. 110.
