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Distributed Optimization Advances In Theories Methods And Applications
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Book Synopsis Distributed Optimization: Advances in Theories, Methods, and Applications by : Huaqing Li
Download or read book Distributed Optimization: Advances in Theories, Methods, and Applications written by Huaqing Li and published by Springer Nature. This book was released on 2020-08-04 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike. Focusing on the natures and functions of agents, communication networks and algorithms in the context of distributed optimization for networked control systems, this book introduces readers to the background of distributed optimization; recent developments in distributed algorithms for various types of underlying communication networks; the implementation of computation-efficient and communication-efficient strategies in the execution of distributed algorithms; and the frameworks of convergence analysis and performance evaluation. On this basis, the book then thoroughly studies 1) distributed constrained optimization and the random sleep scheme, from an agent perspective; 2) asynchronous broadcast-based algorithms, event-triggered communication, quantized communication, unbalanced directed networks, and time-varying networks, from a communication network perspective; and 3) accelerated algorithms and stochastic gradient algorithms, from an algorithm perspective. Finally, the applications of distributed optimization in large-scale statistical learning, wireless sensor networks, and for optimal energy management in smart grids are discussed.
Book Synopsis Distributed Optimization and Learning by : Zhongguo Li
Download or read book Distributed Optimization and Learning written by Zhongguo Li and published by Elsevier. This book was released on 2024-08-06 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Optimization and Learning: A Control-Theoretic Perspective illustrates the underlying principles of distributed optimization and learning. The book presents a systematic and self-contained description of distributed optimization and learning algorithms from a control-theoretic perspective. It focuses on exploring control-theoretic approaches and how those approaches can be utilized to solve distributed optimization and learning problems over network-connected, multi-agent systems. As there are strong links between optimization and learning, this book provides a unified platform for understanding distributed optimization and learning algorithms for different purposes. Provides a series of the latest results, including but not limited to, distributed cooperative and competitive optimization, machine learning, and optimal resource allocation Presents the most recent advances in theory and applications of distributed optimization and machine learning, including insightful connections to traditional control techniques Offers numerical and simulation results in each chapter in order to reflect engineering practice and demonstrate the main focus of developed analysis and synthesis approaches
Book Synopsis Distributed Optimization, Game and Learning Algorithms by : Huiwei Wang
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.
Book Synopsis Distributed Optimization in Networked Systems by : Qingguo Lü
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.
Book Synopsis Large-Scale and Distributed Optimization by : Pontus Giselsson
Download or read book Large-Scale and Distributed Optimization written by Pontus Giselsson and published by Springer. This book was released on 2018-11-11 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians. Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.
Book Synopsis Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers by : Stephen Boyd
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.
Book Synopsis Distributed Optimization with Its Applications to Power Systems by : Tianqiao Zhao
Download or read book Distributed Optimization with Its Applications to Power Systems written by Tianqiao Zhao and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advanced Intelligent Computing Theories and Applications by : De-Shuang Huang
Download or read book Advanced Intelligent Computing Theories and Applications written by De-Shuang Huang and published by Springer. This book was released on 2007-07-31 with total page 1398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, in conjunction with the two volumes CICS 0002 and LNCS 4681, constitutes the refereed proceedings of the Third International Conference on Intelligent Computing held in Qingdao, China, in August 2007. The 139 full papers published here were carefully reviewed and selected from among 2,875 submissions. These papers offer important findings and insights into the field of intelligent computing.
Book Synopsis The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) by : Aboul Ella Hassanien
Download or read book The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) written by Aboul Ella Hassanien and published by Springer. This book was released on 2018-01-25 with total page 726 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the third International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2018, held in Cairo, Egypt, on February 22–24, 2018, and organized by the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic, security, and intelligence swarms and optimization.
Book Synopsis Database Systems for Advanced Applications. DASFAA 2020 International Workshops by : Yunmook Nah
Download or read book Database Systems for Advanced Applications. DASFAA 2020 International Workshops written by Yunmook Nah and published by Springer Nature. This book was released on 2020-09-21 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS 12115 constitutes the workshop papers which were held also online in conjunction with the 25th International Conference on Database Systems for Advanced Applications in September 2020. The complete conference includes 119 full papers presented together with 19 short papers plus 15 demo papers and 4 industrial papers in this volume were carefully reviewed and selected from a total of 487 submissions. DASFAA 2020 presents this year following five workshops: The 7th International Workshop on Big Data Management and Service (BDMS 2020) The 6th International Symposium on Semantic Computing and Personalization (SeCoP 2020) The 5th Big Data Quality Management (BDQM 2020) The 4th International Workshop on Graph Data Management and Analysis (GDMA 2020) The 1st International Workshop on Artificial Intelligence for Data Engineering (AIDE 2020)
Book Synopsis Design of Distributed and Robust Optimization Algorithms. A Systems Theoretic Approach by : Simon Michalowsky
Download or read book Design of Distributed and Robust Optimization Algorithms. A Systems Theoretic Approach written by Simon Michalowsky and published by Logos Verlag Berlin GmbH. This book was released on 2020-04-17 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization algorithms are the backbone of many modern technologies. In this thesis, we address the analysis and design of optimization algorithms from a systems theoretic viewpoint. By properly recasting the algorithm design as a controller synthesis problem, we derive methods that enable a systematic design of tailored optimization algorithms. We consider two specific classes of optimization algorithms: (i) distributed, and (ii) robust optimization algorithms. Concerning (i), we utilize ideas from geometric control in an innovative fashion to derive a novel methodology that enables the design of distributed optimization algorithms under minimal assumptions on the graph topology and the structure of the optimization problem. Concerning (ii), we employ robust control techniques to establish a framework for the analysis of existing algorithms as well as the design of novel robust optimization algorithms with specified guarantees.
Book Synopsis Mathematical Theories of Machine Learning - Theory and Applications by : Bin Shi
Download or read book Mathematical Theories of Machine Learning - Theory and Applications written by Bin Shi and published by Springer. This book was released on 2019-06-12 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle points in non-convex optimization problems. In the second part, the authors propose algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries. In the last part, the authors introduce an novel VAR model with Elastic-Net regularization and its equivalent Bayesian model allowing for both a stable sparsity and a group selection.
Book Synopsis Advanced Parallel and Distributed Computing by : Yuan-Shun Dai
Download or read book Advanced Parallel and Distributed Computing written by Yuan-Shun Dai and published by Nova Publishers. This book was released on 2007 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of parallel and distributed computing is undergoing changes at a breathtaking pace. Networked computers are now omnipresent in virtually every application, from games to sophisticated space missions. The increasing complexity, heterogeneity, largeness, and dynamism of the emerging pervasive environments and associated applications are challenging the advancement of the parallel and distributed computing paradigm. Many novel infrastructures have been or are being created to provide the necessary computational fabric for realising parallel and distributed applications from diverse domains. New models and tools are also being proposed to evaluate and predict the quality of these complicated parallel and distributed systems. Current and recent past efforts, made to provide the infrastructures and models for such applications, have addressed many underlying complex problems and have thus resulted in new tools and paradigms for effectively realising parallel and distributed systems. This book showcases these novel tools and approaches with inputs from relevant experts.
Book Synopsis Computational Modeling, Optimization and Manufacturing Simulation of Advanced Engineering Materials by : Pablo Andrés Muñoz-Rojas
Download or read book Computational Modeling, Optimization and Manufacturing Simulation of Advanced Engineering Materials written by Pablo Andrés Muñoz-Rojas and published by Springer. This book was released on 2016-06-20 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials. Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.
Book Synopsis Distributed Optimization Under Partial Information Using Direct Interaction by : Sun Woo Kim
Download or read book Distributed Optimization Under Partial Information Using Direct Interaction written by Sun Woo Kim and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This research proposes a methodology to solve distributed optimization problems where quasi-autonomous decision entities directly interact with each other for partial information sharing. In the distributed system we study the quasi-autonomy arising from the assumption that each decision entity has complete and unique responsibility for a subset of decision variables. However, when solving a decision problem locally, consideration is given to how the local decisions affect overall system performance such that close-to-optimal solutions are obtained among all participating decision entities. Partial information sharing refers to the fact that no entity has the complete information access needed to solve the optimization problem globally. This condition hinders the direct application of traditional optimization solution methods. In this research, it is further assumed that direct interaction among the decision entities is allowed. This compensates for the lack of complete information access with the interactive exchange of non-private information. The methodology is tested in different application contexts: manufacturing capacity allocation, single machine scheduling, and jobshop scheduling. The experimental results show that the proposed method generates close-to optimal solutions in the tested problem settings.
Book Synopsis Recent Advances in Agent-based Complex Automated Negotiation by : Naoki Fukuta
Download or read book Recent Advances in Agent-based Complex Automated Negotiation written by Naoki Fukuta and published by Springer. This book was released on 2016-03-24 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent advances in Complex Automated Negotiations as a widely studied emerging area in the field of Autonomous Agents and Multi-Agent Systems. The book includes selected revised and extended papers from the 7th International Workshop on Agent-Based Complex Automated Negotiation (ACAN2014), which was held in Paris, France, in May 2014. The book also includes brief introductions about Agent-based Complex Automated Negotiation which are based on tutorials provided in the workshop, and brief summaries and descriptions about the ANAC'14 (Automated Negotiating Agents Competition) competition, where authors of selected finalist agents explain the strategies and the ideas used by them. The book is targeted to academic and industrial researchers in various communities of autonomous agents and multi-agent systems, such as agreement technology, mechanism design, electronic commerce, related areas, as well as graduate, undergraduate, and PhD students working in those areas or having interest in them.
Book Synopsis Advanced Models of Neural Networks by : Gerasimos G. Rigatos
Download or read book Advanced Models of Neural Networks written by Gerasimos G. Rigatos and published by Springer. This book was released on 2014-08-27 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.
