Download or read book Stability and Differential Privacy of Stochastic Gradient Methods written by Zhenhuan Yang (Ph. D. in mathematics) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security written by Edgar Weippl and published by . This book was released on 2016-10-24 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: CCS'16: 2016 ACM SIGSAC Conference on Computer and Communications Security Oct 24, 2016-Oct 28, 2016 Vienna, Austria. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Download or read book Computational Science ICCS 2023 written by Jiří Mikyška and published by Springer Nature. This book was released on 2023-06-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five-volume set LNCS 14073-14077 constitutes the proceedings of the 23rd International Conference on Computational Science, ICCS 2023, held in Prague, Czech Republic, during July 3-5, 2023. The total of 188 full papers and 94 short papers presented in this book set were carefully reviewed and selected from 530 submissions. 54 full and 37 short papers were accepted to the main track; 134 full and 57 short papers were accepted to the workshops/thematic tracks. The theme for 2023, "Computation at the Cutting Edge of Science", highlights the role of Computational Science in assisting multidisciplinary research. This conference was a unique event focusing on recent developments in scalable scientific algorithms, advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms, and tools drive new science through efficient application in physical systems, computational and systems biology, environmental systems, finance, and others.

Download or read book Generalized Stochastic Gradient Learning written by George W. Evans and published by . This book was released on 2005 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG algorithms are sensitive to units of measurement and we show that there is a transformation of variables for which E-stability governs SG stability. GSG algorithms with constant gain have a deeper justification in terms of parameter drift, robustness and risk sensitivity

Download or read book Hands On Differential Privacy written by Ethan Cowan and published by "O'Reilly Media, Inc.". This book was released on 2024-05-16 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases

Download or read book Data Science written by Zhiwen Yu and published by Springer Nature. This book was released on 2023-09-14 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023. The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections: Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis. Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc.

Download or read book Convergence and Stochastic Stability of One step Methods for Stochastic Differential Delay Equations written by Yi Bei Zhang and published by . This book was released on 2004 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Intelligent Computing Technology and Applications written by De-Shuang Huang and published by Springer Nature. This book was released on with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Sharing Confidential Data written by Jörg Drechsler and published by CRC Press. This book was released on 2024-10-09 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature—specifically, synthetic data, formal privacy, and secure computation—can be used to manage trade-offs in disclosure risk and data usefulness. Key features: • Provides overviews of the potential and the limitations of synthetic data, differential privacy, and secure computation • Offers an accessible review of methods for implementing differential privacy, both from methodological and practical perspectives • Presents perspectives from both computer science and statistical science for addressing data confidentiality and privacy • Describes genuine applications of synthetic data, formal privacy, and secure computation to help practitioners implement these approaches The handbook is accessible to both researchers and practitioners who work with confidential data. It requires familiarity with basic concepts from probability and data analysis.

Download or read book Privacy in Statistical Databases written by Josep Domingo-Ferrer and published by Springer. This book was released on 2016-08-30 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2016, held in Dubrovnik, Croatia in September 2016 under the sponsorship of the UNESCO chair in Data Privacy. The 19 revised full papers presented were carefully reviewed and selected from 35 submissions. The scope of the conference is on following topics: tabular data protection; microdata and big data masking; protection using privacy models; synthetic data; remote and cloud access; disclosure risk assessment; co-utile anonymization.

Download or read book Stability of Superimplicit Numerical Methods for Stochastic Differential Equations written by Peter Hall and published by . This book was released on 1994 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Collaborative Computing Networking Applications and Worksharing written by Honghao Gao and published by Springer Nature. This book was released on 2023-01-24 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNICST 460 and 461 constitutes the proceedings of the 18th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2022, held in Hangzhou, China, in October 2022. The 57 full papers presented in the proceedings were carefully reviewed and selected from 171 submissions. The papers are organized in the following topical sections: Recommendation System; Federated Learning and application; Edge Computing and Collaborative working; Blockchain applications; Security and Privacy Protection; Deep Learning and application; Collaborative working; Images processing and recognition.

Download or read book The Algorithmic Foundations of Differential Privacy written by Cynthia Dwork and published by . This book was released on 2014 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.

Download or read book Federated Learning for Future Intelligent Wireless Networks written by Yao Sun and published by John Wiley & Sons. This book was released on 2023-12-27 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Federated Learning for Future Intelligent Wireless Networks Explore the concepts, algorithms, and applications underlying federated learning In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy. Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find: A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FL Comprehensive explorations of wireless communication network design and optimization for federated learning Practical discussions of novel federated learning algorithms and frameworks for future wireless networks Expansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distribution Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.

Download or read book A Survey of Algorithms and Analysis for Stochastic Gradient Methods written by and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stability Stationarity and Boundedness of Some Implicit Numerical Methods for Stochastic Differential Equations written by Henri Schurz and published by . This book was released on 1996 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Gradient Descent in Continuous Time written by Justin Sirignano and published by . This book was released on 2017 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: