Author: Lawrence A. Birnbaum
Publisher: Morgan Kaufmann
ISBN: 1483298175
Category : Computers
Languages : en
Pages : 682

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Book Description
Machine Learning

Author: William W. Cohen
Publisher: Morgan Kaufmann
ISBN: 1483298183
Category : Computers
Languages : en
Pages : 398

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Book Description
Machine Learning Proceedings 1994

Author: Peter Edwards
Publisher: Morgan Kaufmann
ISBN: 1483298531
Category : Computers
Languages : en
Pages : 497

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Book Description
Machine Learning Proceedings 1992

Author: Lawrence A. Birnbaum
Publisher: Morgan Kaufmann
ISBN: 1483298620
Category : Computers
Languages : en
Pages : 361

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Book Description
Machine Learning Proceedings 1993

Author: Armand Prieditis
Publisher: Morgan Kaufmann
ISBN: 1483298663
Category : Computers
Languages : en
Pages : 606

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Book Description
Machine Learning Proceedings 1995

Author: Yves Kodratoff
Publisher: Springer Science & Business Media
ISBN: 9783540538165
Category : Computers
Languages : en
Pages : 554

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Book Description
In this book contemporary knowledge of superconductivity is set against its historical background. First, the highlights of superconductivity research in the twentieth century are reviewed. Further contributions then describe the basic phenomena resulting from the macroscopic quantum state of superconductivity (such as zero resistivity, the Meissner-Ochsenfeld effect, and flux quantization) and review possible mechaniscs, including the classical BCS theory and the more recent alternative theories. The main categories of superconductors - elements, intermetallic phases, chalcogenides, oxides and organic compounds - are described. Common features and differences in their structure and electronic properties are pointed out. This broad overview of superconductivity is completed by a discussion of properties related to the coherence length. Newcomers to the field who seek an overall picture of research in superconductivity, and of the cross-links between its branches, will find this volume especially useful.

Author: Ryszard S. Michalski
Publisher: Morgan Kaufmann
ISBN: 9781558602519
Category : Computers
Languages : en
Pages : 798

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Book Description
Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area. See below for earlier volumes in the series.

Author: Dov M. Gabbay
Publisher: Springer Science & Business Media
ISBN: 9401717338
Category : Mathematics
Languages : en
Pages : 446

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Book Description
This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as logic itself.

Author: Georgios Paliouras
Publisher: Springer
ISBN: 3540446737
Category : Computers
Languages : en
Pages : 334

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Book Description
In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

Author: Michel Bidoit
Publisher: Springer Science & Business Media
ISBN: 9783540540601
Category : Computers
Languages : en
Pages : 116

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Book Description
Methods for the algebraic specification of abstract data types were proposed in the early 1970s in the USA and Canada and became a major research issue in Europe shortly afterwards. Since then the algebraic approach has come to play a central role in research on formal specification and development, as its range of applications was extended to the specification of complete software systems, to the formal description of the program development process, and to the uniform definition of syntax and semantics of programming languages. Today this approach extends beyond just software to the development of integrated hardware and software systems. These flourishing activities in the area of algebraic specifications have led to an abundance of approaches, theories and concepts, which have universal algebra, category theory and logic as a common mathematical basis. This volume is an annotated bibliography which provides an up-to-date overview of past and present work on algebraic specification. No attempt is made to provide a coherent introduction to the topic for beginners; the intention is rather to provide a guide to the current literature for researchers in algebraic specification and neighboring fields. Some indications of how the different approaches are related are included, together with some ideas concerning possible future directions.