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Author : Ronald L. Rivest
Publisher : Morgan Kaufmann
ISBN 13 :
Total Pages : 404 pages
Book Rating : 4.:/5 (318 download)
Download or read book Proceedings of the Second Workshop on Computational Learning Theory written by Ronald L. Rivest and published by Morgan Kaufmann. This book was released on 1989 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Shai Ben-David
Publisher : Springer Science & Business Media
ISBN 13 : 9783540626855
Total Pages : 350 pages
Book Rating : 4.6/5 (268 download)
Download or read book Computational Learning Theory written by Shai Ben-David and published by Springer Science & Business Media. This book was released on 1997-03-03 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description #Includes bibliographical references and index.
Author : David Helmbold
Publisher : Springer
ISBN 13 : 3540445811
Total Pages : 639 pages
Book Rating : 4.5/5 (44 download)
Download or read book Computational Learning Theory written by David Helmbold and published by Springer. This book was released on 2003-06-29 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th Annual and 5th European Conferences on Computational Learning Theory, COLT/EuroCOLT 2001, held in Amsterdam, The Netherlands, in July 2001. The 40 revised full papers presented together with one invited paper were carefully reviewed and selected from a total of 69 submissions. All current aspects of computational learning and its applications in a variety of fields are addressed.
Author :
Publisher :
ISBN 13 :
Total Pages : 316 pages
Book Rating : 4.F/5 ( download)
Download or read book Proceedings of the ... Annual Conference on Computational Learning Theory written by and published by . This book was released on 1998 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Paul Fischer
Publisher : Springer Science & Business Media
ISBN 13 : 3540657010
Total Pages : 311 pages
Book Rating : 4.5/5 (46 download)
Download or read book Computational Learning Theory written by Paul Fischer and published by Springer Science & Business Media. This book was released on 1999-03-17 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th European Conference on Computational Learning Theory, EuroCOLT'99, held in Nordkirchen, Germany in March 1999. The 21 revised full papers presented were selected from a total of 35 submissions; also included are two invited contributions. The book is divided in topical sections on learning from queries and counterexamples, reinforcement learning, online learning and export advice, teaching and learning, inductive inference, and statistical theory of learning and pattern recognition.
Author :
Publisher :
ISBN 13 :
Total Pages : 326 pages
Book Rating : 4.3/5 (91 download)
Download or read book Proceedings of the ... Annual ACM Conference on Computational Learning Theory written by and published by . This book was released on 1998 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : COLT
Publisher : Elsevier
ISBN 13 : 0323137709
Total Pages : 405 pages
Book Rating : 4.3/5 (231 download)
Download or read book COLT Proceedings 1990 written by COLT and published by Elsevier. This book was released on 2012-12-02 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: COLT '90 covers the proceedings of the Third Annual Workshop on Computational Learning Theory, sponsored by the ACM SIGACT/SIGART, University of Rochester, Rochester, New York on August 6-8, 1990. The book focuses on the processes, methodologies, principles, and approaches involved in computational learning theory. The selection first elaborates on inductive inference of minimal programs, learning switch configurations, computational complexity of approximating distributions by probabilistic automata, and a learning criterion for stochastic rules. The text then takes a look at inductive identification of pattern languages with restricted substitutions, learning ring-sum-expansions, sample complexity of PAC-learning using random and chosen examples, and some problems of learning with an Oracle. The book examines a mechanical method of successful scientific inquiry, boosting a weak learning algorithm by majority, and learning by distances. Discussions focus on the relation to PAC learnability, majority-vote game, boosting a weak learner by majority vote, and a paradigm of scientific inquiry. The selection is a dependable source of data for researchers interested in the computational learning theory.
Author : Ryszard S. Michalski
Publisher : Springer Science & Business Media
ISBN 13 : 1461532027
Total Pages : 156 pages
Book Rating : 4.4/5 (615 download)
Download or read book Multistrategy Learning written by Ryszard S. Michalski and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.
Author : COLT
Publisher : Morgan Kaufmann
ISBN 13 : 0080948294
Total Pages : 397 pages
Book Rating : 4.0/5 (89 download)
Download or read book COLT '89 written by COLT and published by Morgan Kaufmann. This book was released on 2014-06-28 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Learning Theory presents the theoretical issues in machine learning and computational models of learning. This book covers a wide range of problems in concept learning, inductive inference, and pattern recognition. Organized into three parts encompassing 32 chapters, this book begins with an overview of the inductive principle based on weak convergence of probability measures. This text then examines the framework for constructing learning algorithms. Other chapters consider the formal theory of learning, which is learning in the sense of improving computational efficiency as opposed to concept learning. This book discusses as well the informed parsimonious (IP) inference that generalizes the compatibility and weighted parsimony techniques, which are most commonly applied in biology. The final chapter deals with the construction of prediction algorithms in a situation in which a learner faces a sequence of trials, with a prediction to be given in each and the goal of the learner is to make some mistakes. This book is a valuable resource for students and teachers.
Author : Leo Breiman
Publisher : SIAM
ISBN 13 : 9780898712964
Total Pages : 740 pages
Book Rating : 4.7/5 (129 download)
Download or read book Probability written by Leo Breiman and published by SIAM. This book was released on 1968-01-01 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Approximation of Large-Scale Dynamical Systems
Author : Stephen Muggleton
Publisher : Morgan Kaufmann
ISBN 13 : 9780125097154
Total Pages : 602 pages
Book Rating : 4.0/5 (971 download)
Download or read book Inductive Logic Programming written by Stephen Muggleton and published by Morgan Kaufmann. This book was released on 1992 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inductive logic programming is a new research area emerging at present. Whilst inheriting various positive characteristics of the parent subjects of logic programming an machine learning, it is hoped that the new area will overcome many of the limitations of its forbears. This book describes the theory, implementations and applications of Inductive Logic Programming.
Author : Pennsy Acm Workshop on Computational Learning Theory 1992 Pittsburgh
Publisher : Assn for Computing Machinery
ISBN 13 : 9780897914970
Total Pages : 468 pages
Book Rating : 4.9/5 (149 download)
Download or read book Proceedings of the Fifth Annual Acm Workshop on Computational Learning Theory written by Pennsy Acm Workshop on Computational Learning Theory 1992 Pittsburgh and published by Assn for Computing Machinery. This book was released on 1992 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Alan L. Meyrowitz
Publisher : Springer Science & Business Media
ISBN 13 : 0585273669
Total Pages : 341 pages
Book Rating : 4.5/5 (852 download)
Download or read book Foundations of Knowledge Acquisition written by Alan L. Meyrowitz and published by Springer Science & Business Media. This book was released on 2007-08-19 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact of successful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain about the methods by which machines and humans might learn, significant progress has been made.
Author : John Shawe-Taylor
Publisher : Springer Science & Business Media
ISBN 13 : 3540222820
Total Pages : 657 pages
Book Rating : 4.5/5 (42 download)
Download or read book Learning Theory written by John Shawe-Taylor and published by Springer Science & Business Media. This book was released on 2004-06-17 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.
Author : Osamu Watanabe
Publisher : Springer
ISBN 13 : 3540467696
Total Pages : 375 pages
Book Rating : 4.5/5 (44 download)
Download or read book Algorithmic Learning Theory written by Osamu Watanabe and published by Springer. This book was released on 2007-03-05 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Algorithmic Learning Theory, ALT'99, held in Tokyo, Japan, in December 1999. The 26 full papers presented were carefully reviewed and selected from a total of 51 submissions. Also included are three invited papers. The papers are organized in sections on Learning Dimension, Inductive Inference, Inductive Logic Programming, PAC Learning, Mathematical Tools for Learning, Learning Recursive Functions, Query Learning and On-Line Learning.
Author : Allen Kent
Publisher : CRC Press
ISBN 13 : 9780824727109
Total Pages : 422 pages
Book Rating : 4.7/5 (271 download)
Download or read book Encyclopedia of Microcomputers written by Allen Kent and published by CRC Press. This book was released on 1993-05-28 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Encyclopedia of Microcomputers serves as the ideal companion reference to the popular Encyclopedia of Computer Science and Technology. Now in its 10th year of publication, this timely reference work details the broad spectrum of microcomputer technology, including microcomputer history; explains and illustrates the use of microcomputers throughout academe, business, government, and society in general; and assesses the future impact of this rapidly changing technology."
Author : Jude W. Shavlik
Publisher : Morgan Kaufmann
ISBN 13 : 9781558601437
Total Pages : 868 pages
Book Rating : 4.6/5 (14 download)
Download or read book Readings in Machine Learning written by Jude W. Shavlik and published by Morgan Kaufmann. This book was released on 1990 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous growth in the field, and this growth promises to continue with valuable contributions to science, engineering, and business. Readings in Machine Learning collects the best of the published machine learning literature, including papers that address a wide range of learning tasks, and that introduce a variety of techniques for giving machines the ability to learn. The editors, in cooperation with a group of expert referees, have chosen important papers that empirically study, theoretically analyze, or psychologically justify machine learning algorithms. The papers are grouped into a dozen categories, each of which is introduced by the editors.
