Algorithmic Learning for Knowledge-Based Systems, Klaus P. Jantke; Steffen Lange

Автор: Klaus P. Jantke; Takeshi Shinohara; Thomas Zeugman
Название: Algorithmic Learning Theory
ISBN: 3540604545 ISBN-13(EAN): 9783540604549
Издательство: Springer
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Описание: These conference proceedings cover current areas related to algorithmic learning theory, in particular the theory of machine learning, design and analysis of learning algorithms, computational logic aspects, inductive inference, learning via queries, and pattern recognition.

Автор: Ioannis Karydis; Spyros Sioutas; Peter Triantafill
Название: Algorithmic Aspects of Cloud Computing
ISBN: 3319299182 ISBN-13(EAN): 9783319299181
Издательство: Springer
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Цена: 5870.00 р.
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Описание: Tutorials.- Algorithmic Aspects of Large-Scale Data Stores.- Software Tools and Distributed Architectures for Cloud-based Data Management.

Автор: Setsuo Arikawa; Klaus P. Jantke
Название: Algorithmic Learning Theory
ISBN: 3540585206 ISBN-13(EAN): 9783540585206
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This volume contains a number of research papers on current aspects of computational learning theory. The contributors focus on algorithmic learning, machine learning, analogical inference, inductive logic, case-based reasoning and formal language learning.

Автор: Klaus P. Jantke; Shigenobu Kobayashi; Etsuji Tomit
Название: Algorithmic Learning Theory
ISBN: 3540573704 ISBN-13(EAN): 9783540573708
Издательство: Springer
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Цена: 12157.00 р.
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Описание: This volume contains all the papers that were presented at the Fourth Workshop on Algorithmic Learning Theory, held in Tokyo in November 1993. It is organized into parts on inductive logic and inference; approximate learning; query learning; explanation-based learning; and new learning paradigms.

Автор: Shuji Doshita; Koichi Furukawa; Klaus P. Jantke; T
Название: Algorithmic Learning Theory - ALT `92
ISBN: 3540573690 ISBN-13(EAN): 9783540573692
Издательство: Springer
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Описание: This volume contains the research papers presented at the 3rd Workshop on Algorithmic Learning Theory, held in Tokyo, Japan, in October 1992. It is organized into sections on neural networks, learning via query, inductive inference, analogical reasoning and approximate learning.

Автор: Michael M. Richter; Carl H. Smith; Rolf Wiehagen;
Название: Algorithmic Learning Theory
ISBN: 354065013X ISBN-13(EAN): 9783540650133
Издательство: Springer
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Цена: 10480.00 р.
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Описание: A collection of papers from the 9th International Conference on Algorithmic Learning Theory. They are organized in sections on inductive logic programming and data mining, inductive inference, learning via queries, prediction algorithms, inductive logic programming and learning formal languages.

Автор: Sanjay Jain; R?mi Munos; Frank Stephan; Thomas Zeu
Название: Algorithmic Learning Theory
ISBN: 3642409342 ISBN-13(EAN): 9783642409349
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the proceedings of the 24th International Conference on Algorithmic Learning Theory, ALT 2013, held in Singapore in October 2013, and co-located with the 16th International Conference on Discovery Science, DS 2013.

Автор: A. van Wijngaarden; B.J. Mailloux; J.E.L. Peck; C.
Название: Revised Report on the Algorithmic Language Algol 68
ISBN: 3540075925 ISBN-13(EAN): 9783540075929
Издательство: Springer
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Автор: Ulrich Faigle; W. Kern; G. Still
Название: Algorithmic Principles of Mathematical Programming
ISBN: 9048161177 ISBN-13(EAN): 9789048161171
Издательство: Springer
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Описание: Algorithmic Principles of Mathematical Programming investigates the mathematical structures and principles underlying the design of efficient algorithms for optimization problems. Recent advances in algorithmic theory have shown that the traditionally separate areas of discrete optimization, linear programming, and nonlinear optimization are closely linked. This book offers a comprehensive introduction to the whole subject and leads the reader to the frontiers of current research. The prerequisites to use the book are very elementary. All the tools from numerical linear algebra and calculus are fully reviewed and developed. Rather than attempting to be encyclopedic, the book illustrates the important basic techniques with typical problems. The focus is on efficient algorithms with respect to practical usefulness. Algorithmic complexity theory is presented with the goal of helping the reader understand the concepts without having to become a theoretical specialist. Further theory is outlined and supplemented with pointers to the relevant literature.
The book is equally suited for self-study for a motivated beginner and for a comprehensive course on the principles of mathematical programming within an applied mathematics or computer science curriculum at advanced undergraduate or graduate level. The presentation of the material is such that smaller modules on discrete optimization, linear programming, and nonlinear optimization can easily be extracted separately and used for shorter specialized courses on these subjects.

Автор: Martin Hoefer
Название: Algorithmic Game Theory
ISBN: 3662484323 ISBN-13(EAN): 9783662484326
Издательство: Springer
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Цена: 6708.00 р.
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Описание: This book constitutes the refereed proceedings of the 8th International Symposium on Algorithmic Game Theory, SAGT 2015, held in Saarbrucken, Germany, in September 2015. The 22 full papers presented together with one extended abstract and 6 brief announcements were carefully reviewed and selected from 63 submissions.