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Algorithmic aspects of resource allocation and multiwinner voting: theory and…
This thesis is concerned with investigating elements of computational social choice in the light of real-world applications. We contribute to a better understanding of the areas of fair allocation and multiwinner voting. For both areas, inspired by real-world scenarios, we propose several new notions and extensions of existing models. Then, we analyze the complexity of answering the computation…
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- 241 hlm; ill., lamp.,
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Artificial Intelligence and the Internet of Things
Through algorithms and artificial intelligence (AI), objects and digital services now demonstrate new skills they did not have before, right up to replacing human activity through pre-programming or by making their own decisions. As part of the internet of things, AI applications are already widely used today, for example in language processing, image recognition and the tracking and processing…
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- 9781911534822
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- online resource
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- CAMRI Policy Briefs,
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Abrasive Technology
The subject matter of this book is the information on the abrasive technology methods, the characteristics of the methods (for example, the technological parameters, tools, and machines), innovative methods, characteristics of surface structure and surface properties after this type of mechanical process, and application in various industrial branches and other technical and technological domai…
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- 9781838816803
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- oer.unej.ac.id
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Today's TBB Today's TBB = C++ Parallel Programming with Threading Building B…
This open-access book serves as a comprehensive guide for C++ programmers looking to master Threading Building Blocks (TBB). Authored by two experts in TBB and parallel programming, the book distills decades of collective experience in developing and teaching parallel programming concepts, presenting insights in a clear and accessible manner. Today’s TBB starts with foundational principles, …
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- 9798868812705
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- LXXI, 447 hlm,: ill, lamp; 21 cm
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Boosting: Foundations and Algorithms
A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. …
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- 9780262301183
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- 1 online resource (xv, 526 pages) :illustrations
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Genetic programming 1996 : Proceedings of the First Annual Conference, July 2…
Genetic programming is a domain-independent method for automatic programming that evolves computer programs that solve, or approximately solve, problems. Starting with a primordial ooze of thousands of randomly created computer programs composed of functions and terminals appropriate to a problem, a population of programs is progressively evolved over many generations using the Darwinian princi…
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- 9780262315876
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- 1 online resource (xviii, 568 pages) : illustrations.
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- 005 GEN
Nearest-neighbor methods in learning and vision :theory and practice
" ... held in Whistler, British Columbia ... annual conference on Neural Information Processing Systems (NIPS) in December 2003"--Preface.Regression and classification methods based on similarity of the input to stored examples have not been widely used in applications involving very large sets of high-dimensional data. Recent advances in computational geometry and machine learning, however, ma…
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- 9780262256957
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- 1 online resource (vi, 252 pages) :illustrations.
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Algorithms
In the tradition of Real World Algorithms: A Beginner's Guide, Panos Louridas is back to introduce algorithms in an accessible manner, utilizing various examples to explain not just what algorithms are but how they work. Digital technology runs on algorithms, sets of instructions that describe how to do something efficiently. Application areas range from search engines to tournament scheduling,…
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- 9780262358675
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- 1 online resource
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Learning Kernel Classifiers: Theory and Algorithms
Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This…
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- 9780262256339
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Online stochastic combinatorial optimization
"Online decision making under uncertainty and time constraints represents one of the most challenging problems for robust intelligent agents. In an increasingly dynamic, interconnected, and real-time world, intelligent systems must adapt dynamically to uncertainties, update existing plans to accommodate new requests and events, and produce high-quality decisions under severe time constraints. S…
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- 9780262257152
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- 1 online resource (xiii, 232 pages) :illustrations
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