Adaptive Learning by Genetic Algorithms, Herbert Dawid

Автор: Michaelis
Название: Solving Large Scale Learning Tasks. Challenges and Algorithms
ISBN: 3319417053 ISBN-13(EAN): 9783319417059
Издательство: Springer
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Цена: 52170.00 T
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Описание: Morik worked in and presents various researchers with whom she collaborated. The 23 refereed articles in this Festschrift volume provide challenges and solutions from theoreticians and practitioners on data preprocessing, modeling, learning, and evaluation.

Автор: W. Hackbusch; G. Wittum
Название: Adaptive Methods — Algorithms, Theory and Applications
ISBN: 3528076461 ISBN-13(EAN): 9783528076467
Издательство: Springer
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Цена: 81050.00 T
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Описание: This volume contains 18 papers presented at the Kiel Seminar in 1993. The Kiel Seminars are well-known, and cover special areas in numerical methods for partial differential equations, numerical linear algebra, numerical methods for integral equations and related areas.

Автор: Enrique Alba; Bernabe Dorronsoro
Название: Cellular Genetic Algorithms
ISBN: 1441945946 ISBN-13(EAN): 9781441945945
Издательство: Springer
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Цена: 102480.00 T
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Описание: Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel emphasis on both theory and practice.

Автор: Masatoshi Sakawa
Название: Genetic Algorithms and Fuzzy Multiobjective Optimization
ISBN: 146135594X ISBN-13(EAN): 9781461355946
Издательство: Springer
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Цена: 139750.00 T
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Автор: Chen Shu Heng
Название: Genetic Algorithms and Genetic Programming in Computational
ISBN: 1461352622 ISBN-13(EAN): 9781461352624
Издательство: Springer
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Цена: 167700.00 T
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Описание: After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance.

Автор: Verbert
Название: Adaptive and Adaptable Learning
ISBN: 3319451529 ISBN-13(EAN): 9783319451527
Издательство: Springer
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Цена: 76400.00 T
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Описание: This book constitutes the proceedings of the 11th European Conference on Technology Enhanced Learning, EC-TEL 2016, held in Lyon, France, in September 2016. The 26 full papers, 23 short papers, 8 demo papers, and 33 poster papers presented in this volume were carefully reviewed and selected from 148 submissions.

Автор: Niedermeier, Rolf
Название: Invitation to fixed-parameter algorithms
ISBN: 0198566077 ISBN-13(EAN): 9780198566076
Издательство: Oxford Academ
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Цена: 145200.00 T
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Описание: An application-oriented introduction to the highly topical area of the development and analysis of efficient fixed-parameter algorithms for hard problems. Aimed at graduate and research mathematicians, algorithm designers, and computer scientists, it provides a fresh view on this highly innovative field of algorithmic research.

Автор: Korte, Bernhard, Vygen, Jens
Название: Combinatorial Optimization (algorithms and Combinatorics 21) 5th ed.
ISBN: 3642244874 ISBN-13(EAN): 9783642244872
Издательство: Springer
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Цена: 60510.00 T
Наличие на складе: Невозможна поставка.
Описание: This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This fifth edition has again been updated, revised, and significantly extended, with more than 60 new exercises and new material on various topics, including Cayley's formula, blocking flows, faster b-matching separation, multidimensional knapsack, multicommodity max-flow min-cut ratio, and sparsest cut. Thus, this book represents the state of the art of combinatorial optimization.

Автор: Lo Andrew W.
Название: Adaptive Markets: Financial Evolution at the Speed of Thought
ISBN: 0691135142 ISBN-13(EAN): 9780691135144
Издательство: Wiley
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Цена: 33790.00 T
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Описание:

A new, evolutionary explanation of markets and investor behavior

Half of all Americans have money in the stock market, yet economists can't agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe--and as financial bubbles, crashes, and crises suggest. This is one of the biggest debates in economics and the value or futility of investment management and financial regulation hang on the outcome. In this groundbreaking book, Andrew Lo cuts through this debate with a new framework, the Adaptive Markets Hypothesis, in which rationality and irrationality coexist.

Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency isn't wrong but merely incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo's new paradigm explains how financial evolution shapes behavior and markets at the speed of thought--a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation.

A fascinating intellectual journey filled with compelling stories, Adaptive Markets starts with the origins of market efficiency and its failures, turns to the foundations of investor behavior, and concludes with practical implications--including how hedge funds have become the Gal pagos Islands of finance, what really happened in the 2008 meltdown, and how we might avoid future crises.

An ambitious new answer to fundamental questions in economics, Adaptive Markets is essential reading for anyone who wants to know how markets really work.

Автор: Pawel Cichosz
Название: Data Mining Algorithms: Explained Using R
ISBN: 111833258X ISBN-13(EAN): 9781118332580
Издательство: Wiley
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Цена: 66470.00 T
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Описание: Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles.

Название: Practical Analysis of Algorithms
ISBN: 331909887X ISBN-13(EAN): 9783319098876
Издательство: Springer
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Цена: 41920.00 T
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Описание: This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts.

Автор: Ito Kazufumi, Jin Bangti
Название: Inverse Problems: Tikhonov Theory and Algorithms
ISBN: 9814596191 ISBN-13(EAN): 9789814596190
Издательство: World Scientific Publishing
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Цена: 118270.00 T
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Описание:

Inverse problems arise in practical applications whenever one needs to deduce unknowns from observables. This monograph is a valuable contribution to the highly topical field of computational inverse problems. Both mathematical theory and numerical algorithms for model-based inverse problems are discussed in detail. The mathematical theory focuses on nonsmooth Tikhonov regularization for linear and nonlinear inverse problems. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian inference.

The book offers a comprehensive treatment of modern techniques, and seamlessly blends regularization theory with computational methods, which is essential for developing accurate and efficient inversion algorithms for many practical inverse problems.

It demonstrates many current developments in the field of computational inversion, such as value function calculus, augmented Tikhonov regularization, multi-parameter Tikhonov regularization, semismooth Newton method, direct sampling method, uncertainty quantification and approximate Bayesian inference. It is written for graduate students and researchers in mathematics, natural science and engineering.