Author: Dr P. SrinivasaRao
Publisher: Lulu.com
ISBN: 1387388762
Category :
Languages : en
Pages : 97

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Author: Chu-Min Li
Publisher: Springer Nature
ISBN: 303080223X
Category : Computers
Languages : en
Pages : 564

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Book Description
This book constitutes the proceedings of the 24th International Conference on Theory and Applications of Satisfiability Testing, SAT 2021, which took place in Barcelona, Spain, in July 2021. The 37 full papers presented in this volume were carefully reviewed and selected from 73 submissions. They deal with theory and applications of the propositional satisfiability problem, broadly construed. Aside from plain propositional satisfiability, the scope of the meeting includes Boolean optimization, including MaxSAT and pseudo-Boolean (PB) constraints, quantified Boolean formulas (QBF), satisfiability modulo theories (SMT), and constraint programming (CP) for problems with clear connections to Boolean reasoning.

Author: Hassan, Jahan
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 425

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Book Description
Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy. This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond.

Author:
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN:
Category : Client/server computing
Languages : en
Pages : 260

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Book Description
This text constitutes the proceedings from the International Workshop on Autonomous Decentralized Systems (IWADS2000) that took place in 2000. Topics covered include flexible and autonomous service replication technique, and information searching in autonomous mobile agent groups.

Author: Narayan Desai
Publisher: Springer
ISBN: 3662437791
Category : Computers
Languages : en
Pages : 193

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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 17th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2013, held Boston, MA, USA, in May 2013. The 10 revised papers presented were carefully reviewed and selected from 20 submissions. The papers cover the following topics parallel scheduling for commercial environments, scientific computing, supercomputing and cluster platforms.

Author: Chandra Kopparapu
Publisher: John Wiley & Sons
ISBN: 0471421286
Category : Computers
Languages : en
Pages : 224

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Book Description
From an industry insider--a close look at high-performance,end-to-end switching solutions Load balancers are fast becoming an indispensable solution forhandling the huge traffic demands of the Web. Their ability tosolve a multitude of network and server bottlenecks in the Internetage ranges from dramatic improvements in server farm scalability toremoving the firewall as a network bottleneck. This book provides adetailed, up-to-date, technical discussion of this fast-growing,multibillion dollar market, covering the full spectrum oftopics--from server and firewall load balancing to transparentcache switching to global server load balancing. In the process,the author delivers insight into the way new technologies aredeployed in network infrastructure and how they work. Written by anindustry expert who hails from a leading Web switch vendor, thisbook will help network and server administrators improve thescalability, availability, manageability, and security of theirservers, firewalls, caches, and Web sites.

Author: Frans A. Oliehoek
Publisher: Springer
ISBN: 3319289292
Category : Computers
Languages : en
Pages : 134

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Book Description
This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.

Author: Kai Hwang
Publisher: Morgan Kaufmann
ISBN: 0128002042
Category : Computers
Languages : en
Pages : 672

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Book Description
Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online

Author: Qiang Qiang Yang
Publisher: Springer Nature
ISBN: 3031015851
Category : Computers
Languages : en
Pages : 189

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Book Description
How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.

Author: Stephen Boyd
Publisher: Now Publishers Inc
ISBN: 160198460X
Category : Computers
Languages : en
Pages : 138

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Book Description
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.