Описание: This book constitutes the refereed proceedings of the 14th International Conference on Algorithmic Learning Theory, ALT 2003, held in Sapporo, Japan in October 2003.The 19 revised full papers presented together with 2 invited papers and abstracts of 3 invited talks were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on inductive inference, learning and information extraction, learning with queries, learning with non-linear optimization, learning from random examples, and online prediction.
Описание: This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006.The 24 revised full papers presented together with the abstracts of 5 invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning; they address topics such as query models, on-line learning, inductive inference, algorithmic forecasting, boosting, support vector machines, kernel methods, reinforcement learning, and statistical learning models.
Описание: This book constitutes the refereed proceedings of the 7th International Algorithmic Number Theory Symposium, ANTS 2006, held in Berlin, Germany in July 2006.The 37 revised full papers presented together with 4 invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on algebraic number theory, analytic and elementary number theory, lattices, curves and varieties over fields of characteristic zero, curves over finite fields and applications, and discrete logarithms.
Описание: This book constitutes the refereed proceedings of the 16th International Conference on Algorithmic Learning Theory, ALT 2005, held in Singapore in October 2005.The 30 revised full papers presented together with 5 invited papers and an introduction by the editors were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on kernel-based learning, bayesian and statistical models, PAC-learning, query-learning, inductive inference, language learning, learning and logic, learning from expert advice, online learning, defensive forecasting, and teaching.
Описание: This book treats the Mathematics of many important areas in digital information processing. It covers, in a unified presentation, five topics: Data Compression, Cryptography, Sampling (Signal Theory), Error Control Codes, Data Reduction. The thematic choices are practice-oriented. So, the important final part of the book deals with the Discrete Cosine Transform and the Discrete Wavelet Transform, acting in image compression. The presentation is dense, the examples and numerous exercises are concrete. The pedagogic architecture follows increasing mathematical complexity. A read-and-learn book on Concrete Mathematics, for teachers, students and practitioners in Electronic Engineering, Computer Science and Mathematics.
Описание: This book constitutes the refereed proceedings of the 15th International Conference on Algorithmic Learning Theory, ALT 2004, held in Padova, Italy in October 2004.The 29 revised full papers presented together with 5 invited papers and 3 tutorial summaries were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on inductive inference, PAC learning and boosting, statistical supervised learning, online sequence learning, approximate optimization algorithms, logic based learning, and query and reinforcement learning.
Автор: Gregory. J. Chaitin Название: Algorithmic Information Theory ISBN: 0521616042 ISBN-13(EAN): 9780521616041 Издательство: Cambridge Academ Рейтинг: Цена: 4600 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chaitin, the inventor of algorithmic information theory, presents in this book the strongest possible version of G?¶del's incompleteness theorem, using an information theoretic approach based on the size of computer programs. One half of the book is concerned with studying the halting probability of a universal computer if its program is chosen by tossing a coin. The other half is concerned with encoding the halting probability as an algebraic equation in integers, a so-called exponential diophantine equation.
Автор: Roughgarden Название: Twenty Lectures on Algorithmic Game Theory ISBN: 131662479X ISBN-13(EAN): 9781316624791 Издательство: Cambridge Academ Рейтинг: Цена: 2990 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Описание: The book presents in a mathematical clear way the fundamentals of algorithmic information theory and a few selected applications. This 2nd edition presents new and important results obtained in recent years: the characterization of computable enumerable random reals, the construction of an Omega Number for which ZFC cannot determine any digits, and the first successful attempt to compute the exact values of 64 bits of a specific Omega Number. Finally, the book contains a discussion of some interesting philosophical questions related to randomness and mathematical knowledge. "Professor Calude has produced a first-rate exposition of up-to-date work in information and randomness." D.S. Bridges, Canterbury University, co-author, with Errett Bishop, of Constructive Analysis;"The second edition of this classic work is highly recommended to anyone interested in algorithmic information and randomness." G.J. Chaitin, IBM Research Division, New York, author of Conversations with a Mathematician; "This book is a must for a comprehensive introduction to algorithmic information theory and for anyone interested in its applications in the natural sciences." K. Svozil, Technical University of Vienna, author of Randomness & Undecidability in Physics
Автор: Dobrushkin Название: Methods in Algorithmic Analysis ISBN: 1420068296 ISBN-13(EAN): 9781420068290 Издательство: Taylor&Francis Рейтинг: Цена: 19058 р. Наличие на складе: Поставка под заказ.
Описание: Accompanied by more than 1,000 examples and exercises, this comprehensive, classroom-tested text presents numerous theories, techniques, and methods used for analyzing algorithms. It includes basic material on combinatorics and probability that can be used for students with weak backgrounds. It presents information on asymptotics not usually found in similar books, including Rice’s method, the Euler and Boole summation formulas, and recurrences. The author offers tutorials throughout the text on topics as diverse as continued fractions, functions of a complex variable, numerical calculations, and Stieltjes integration. An appendix contains a comprehensive collection of useful formulas.
Описание: This book constitutes the thoroughly refereed post-proceedings of the Third Workshop on Combinatorial and Algorithmic Aspects of Networking, held in Chester, UK in July 2006, co-located with the 13th Colloquium on Structural Information and Communication Complexity, SIROCCO 2006.The 10 revised full papers together with 1 invited lecture presented were carefully reviewed and selected from a total of 22 submissions. The topics covered range from the Web graph to game theory to string matching, all in the context of large-scale networks.
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