Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
Download or read book Self Organizing Architectures written by Danny Weyns and published by Springer Science & Business Media. This book was released on 2010-07-15 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields.
Download or read book Distributed Parallel and Biologically Inspired Systems written by Mike Hinchey and published by Springer. This book was released on 2010-08-06 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: st This volume contains the proceedings of two conferences held as part of the 21 IFIP World Computer Congress in Brisbane, Australia, 20–23 September 2010. th The first part of the book presents the proceedings of DIPES 2010, the 7 IFIP Conference on Distributed and Parallel Embedded Systems. The conference, int- duced in a separate preface by the Chairs, covers a range of topics from specification and design of embedded systems through to dependability and fault tolerance. rd The second part of the book contains the proceedings of BICC 2010, the 3 IFIP Conference on Biologically-Inspired Collaborative Computing. The conference is concerned with emerging techniques from research areas such as organic computing, autonomic computing and self-adaptive systems, where inspiraton for techniques - rives from exhibited behaviour in nature and biology. Such techniques require the use of research developed by the DIPES community in supporting collaboration over multiple systems. We hope that the combination of the two proceedings will add value for the reader and advance our related work.
Download or read book Machine Learning Approach for Cloud Data Analytics in IoT written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-07-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Download or read book Optimization Algorithms for Distributed Machine Learning written by Gauri Joshi and published by Springer Nature. This book was released on 2022-11-25 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.
Download or read book Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control written by Yongzhao Hua and published by Springer Nature. This book was released on with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scaling Up Machine Learning written by Ron Bekkerman and published by Cambridge University Press. This book was released on 2012 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
Download or read book Decentralized Systems and Distributed Computing written by Sandhya Avasthi and published by John Wiley & Sons. This book was released on 2024-07-31 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive exploration of next-generation internet, distributed systems, and distributed computing, offering valuable insights into their impact on society and the future of technology. The use of distributed systems is a big step forward in IT and computer science. As the number of tasks that depend on each other grows, a single machine can no longer handle all of them. Distributed computing is better than traditional computer settings in several ways. Distributed systems reduce the risks of a single point of failure, making them more reliable and able to handle mistakes. Most modern distributed systems are made to be scalable, which means that processing power can be added on the fly to improve performance. The internet of the future is meant to give us freedom and choices, encourage diversity and decentralization, and make it easier for people to be creative and do research. By making the internet more three-dimensional and immersive, the metaverse could introduce more ways to use it. Some people have expressed negative things about the metaverse, and there is much uncertainty regarding its future. Analysts in the field have pondered if the metaverse will differ much from our current digital experiences, and if so, whether people will be willing to spend hours per day exploring virtual space while wearing a headset. This book will look at the different aspects of the next-generation internet, distributed systems, distributed computing, and their effects on society as a whole.
Download or read book Decentralized Frameworks for Future Power Systems written by Mohsen Parsa Moghaddam and published by Academic Press. This book was released on 2022-05-12 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decentralized Frameworks for Future Power Systems: Operation, Planning and Control Perspectives is the first book to consider the principles and applications of decentralized decision-making in future power networks. The work opens by defining the emerging power system network as a system-of-systems (SoS), exploring the guiding principles behind optimal solutions for operation and planning problems. Chapters emphasize the role of regulations, prosumption behaviors, and the implementation of transactive energy processes as key components in decentralizing power systems. Contributors explore local markets, distribution system operation and proactive load management. The role of cryptocurrencies in smoothing transactive distributional challenges are presented. Final sections cover energy system planning, particularly in terms of consumer smart meter technologies and distributed optimization methods, including artificial intelligence, meta-heuristic, heuristic, mathematical and hybrid approaches. The work closes by considering decentralization across the cybersecurity, distributed control, market design and power quality optimization vertices. - Develops a novel framework for transactive energy management to enhance flexibility in future power systems - Explores interactions between multiple entities in local power markets based on a distributed optimization approach - Focuses on practical optimization, planning and control of smart grid systems towards decentralized decision-making
Download or read book Machine Learning and Knowledge Discovery in Databases Research Track written by Albert Bifet and published by Springer Nature. This book was released on with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Distributed Optimization in Networked Systems written by Qingguo Lü and published by Springer Nature. This book was released on 2023-02-08 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on improving the performance (convergence rate, communication efficiency, computational efficiency, etc.) of algorithms in the context of distributed optimization in networked systems and their successful application to real-world applications (smart grids and online learning). Readers may be particularly interested in the sections on consensus protocols, optimization skills, accelerated mechanisms, event-triggered strategies, variance-reduction communication techniques, etc., in connection with distributed optimization in various networked systems. This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike.
Download or read book Distributed Optimization Game and Learning Algorithms written by Huiwei Wang and published by Springer Nature. This book was released on 2021-01-04 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.
Download or read book First order and Stochastic Optimization Methods for Machine Learning written by Guanghui Lan and published by Springer Nature. This book was released on 2020-05-15 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.
Download or read book Distributed Computing to Blockchain written by Rajiv Pandey and published by Elsevier. This book was released on 2023-04-08 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Computing to Blockchain: Architecture, Technology, and Applications provides researchers, computer scientists, and data scientists with a comprehensive and applied reference covering the evolution of distributed systems computing into blockchain and associated systems. Divided into three major sections, the book explores the basic topics in the blockchain space extending from distributed systems architecture, distributed ledger, decentralized web to introductory aspects of cryptoeconomics (cryptography and economics) of decentralized applications. The book further explores advanced concepts such as smart contracts; distributed token mining, initial coin offerings; proof of work; public, private, and other blockchains; cryptography; security; and blockchains. The book goes on to review byzantine fault tolerance, distributed ledgers versus blockchains, and blockchain protocols. The final section covers multiple use cases and applications of distributed computing and the future directions for blockchains. - Presented as a focused reference handbook describing the evolution of distributed systems, blockchain, and consensus algorithms emphasizing the architectural and functional aspects - Integrates the various concepts of cryptography in blockchain and further extends to blockchain forensics - Provides insight and detailed Interpretation of algorithms for consensus in blockchains
Download or read book Computational Logistics written by Alexander Garrido and published by Springer Nature. This book was released on with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Unix Programming Environment written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of International Conference on Computing and Communication Networks written by Ali Kashif Bashir and published by Springer Nature. This book was released on 2022-07-08 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected peer-reviewed papers presented at the International Conference on Computing and Communication Networks (ICCCN 2021), held at Manchester Metropolitan University, United Kingdom, during 19–20 November 2021. The book covers topics of network and computing technologies, artificial intelligence and machine learning, security and privacy, communication systems, cyber physical systems, data analytics, cyber security for Industry 4.0, and smart and sustainable environmental systems.
