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Machine Learning
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.
Introduction to Machine Learning
A textbook suitable for undergraduate courses in machine learning and related topics, this book provides a broad survey of the field. Generous exercises and examples give students a firm grasp of the concepts and techniques of this rapidly developing, challenging subject. Introduction to Machine Learning synthesizes and clarifies the work of leading researchers, much of which is otherwise available only in undigested technical reports, journals, and conference proceedings. Beginning with an overview suitable for undergraduate readers, Kodratoff establishes a theoretical basis for machine learning and describes its technical concepts and major application areas. Relevant logic programming examples are given in Prolog. Introduction to Machine Learning is an accessible and original introduction to a significant research area.
Machine Learning: ECML-94
This volume contains the proceedings of the European Conference on Machine Learning 1994, which continues the tradition of earlier meetings and which is a major forum for the presentation of the latest and most significant results in machine learning. Machine learning is one of the most important subfields of artificial intelligence and computer science, as it is concerned with the automation of learning processes. This volume contains two invited papers, 19 regular papers, and 25 short papers carefully reviewed and selected from in total 88 submissions. The papers describe techniques, algorithms, implementations, and experiments in the area of machine learning.
Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society
This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 16th annual meeting of the Cognitive Science Society.
Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration
"This book provides relevant theoretical frameworks and the latest empirical research findings in biomedicine information retrieval as it pertains to linguistic granularity"--Provided by publisher.
Logic Program Synthesis and Transformation
Logic program synthesis and transformation are topics of central importance to the software industry. The demand for software can not be met by the current supply, in terms of volume, complexity, or reliability. The most promising solution seems to be the increased automation of software production: programmer productivity would improve, and correctness could be ensured by the application of mathematical methods. Because of their mathematical foundations, logic programs lend themselves particularly well to machine-assisted development techniques, and therefore to automation. This volume contains the proceedings of the second International Workshop on Logic Program Synthesis and Transformatio...
Quality Measures in Data Mining
This book presents recent advances in quality measures in data mining.
Aspects and Prospects of Theoretical Computer Science
This volume contains the texts of the tutorial lecture, five invited lectures and twenty short communications contributed for presentation at the Sixth International Meeting of Young Computer Scientists, IMYCS '90. The aim of these meetings is threefold: (1) to inform on newest trends, results, and problems in theoretical computer science and related fields through a tutorial and invited lectures delivered by internationally distinguished speakers, (2) to provide a possibility for beginners in scientific work to present and discuss their results, and (3) to create an adequate opportunity for establishing first professional relations among the participants.
Methodology and Tools in Knowledge-Based Systems
This two-volume set constitutes the refereed proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE-98, held in Benicassim, Castellon, Spain, in June 1998.The two volumes present a total of 187 revised full papers selected from 291 submissions. In accordance with the conference, the books are devoted to new methodologies, knowledge modeling and hybrid techniques. The papers explore applications from virtually all subareas of AI including knowledge-based systems, fuzzyness and uncertainty, formal reasoning, neural information processing, multiagent systems, perception, robotics, natural language processing, machine learning, supervision and control systems, etc..
