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Optimization Over Time

Optimization Over Time
Author: Peter Whittle
Publisher:
Total Pages: 338
Release: 1982
Genre: Dynamic programming
ISBN:

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Optimization Over Time

Optimization Over Time
Author: Peter Whittle
Publisher:
Total Pages: 317
Release: 1982
Genre:
ISBN:

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Algorithms for Convex Optimization

Algorithms for Convex Optimization
Author: Nisheeth K. Vishnoi
Publisher: Cambridge University Press
Total Pages: 314
Release: 2021-10-07
Genre: Computers
ISBN: 1108633994

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In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods. The goal of this self-contained book is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds. This modern text explains the success of these algorithms in problems of discrete optimization, as well as how these methods have significantly pushed the state of the art of convex optimization itself.


Optimization Over Time

Optimization Over Time
Author: Peter Whittle
Publisher:
Total Pages: 328
Release: 1981
Genre:
ISBN:

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Multi-agent Optimization

Multi-agent Optimization
Author: Angelia Nedić
Publisher: Springer
Total Pages: 310
Release: 2018-11-01
Genre: Business & Economics
ISBN: 3319971425

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This book contains three well-written research tutorials that inform the graduate reader about the forefront of current research in multi-agent optimization. These tutorials cover topics that have not yet found their way in standard books and offer the reader the unique opportunity to be guided by major researchers in the respective fields. Multi-agent optimization, lying at the intersection of classical optimization, game theory, and variational inequality theory, is at the forefront of modern optimization and has recently undergone a dramatic development. It seems timely to provide an overview that describes in detail ongoing research and important trends. This book concentrates on Distributed Optimization over Networks; Differential Variational Inequalities; and Advanced Decomposition Algorithms for Multi-agent Systems. This book will appeal to both mathematicians and mathematically oriented engineers and will be the source of inspiration for PhD students and researchers.


Handbook of Formal Optimization

Handbook of Formal Optimization
Author: Anand J. Kulkarni
Publisher: Springer Nature
Total Pages: 1406
Release:
Genre:
ISBN: 9819738202

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Real-Time Rendering

Real-Time Rendering
Author: Tomas Akenine-Möller
Publisher: CRC Press
Total Pages: 1046
Release: 2019-01-18
Genre: Computers
ISBN: 1315362007

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Thoroughly revised, this third edition focuses on modern techniques used to generate synthetic three-dimensional images in a fraction of a second. With the advent of programmable shaders, a wide variety of new algorithms have arisen and evolved over the past few years. This edition discusses current, practical rendering methods used in games and other applications. It also presents a solid theoretical framework and relevant mathematics for the field of interactive computer graphics, all in an approachable style. The authors have made the figures used in the book available for download for fair use.:Download Figures. Reviews Rendering has been a required reference for professional graphics practitioners for nearly a decade. This latest edition is as relevant as ever, covering topics from essential mathematical foundations to advanced techniques used by today’s cutting edge games. -- Gabe Newell, President, Valve, May 2008 Rendering ... has been completely revised and revamped for its updated third edition, which focuses on modern techniques used to generate three-dimensional images in a fraction of the time old processes took. From practical rendering for games to math and details for better interactive applications, it's not to be missed. -- The Bookwatch, November 2008 You'll get brilliantly lucid explanations of concepts like vertex morphing and variance shadow mapping—as well as a new respect for the incredible craftsmanship that goes into today's PC games. -- Logan Decker, PC Gamer Magazine , February 2009


Distributed Optimization: Advances in Theories, Methods, and Applications

Distributed Optimization: Advances in Theories, Methods, and Applications
Author: Huaqing Li
Publisher: Springer Nature
Total Pages: 243
Release: 2020-08-04
Genre: Technology & Engineering
ISBN: 9811561095

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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.