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EBookClubs

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Book An Introduction to Computational Learning Theory

Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Book A Probabilistic Theory of Pattern Recognition

Download or read book A Probabilistic Theory of Pattern Recognition written by Luc Devroye and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.

Book Computational Learning Theory

Download or read book Computational Learning Theory written by Paul Vitanyi and published by Springer Science & Business Media. This book was released on 1995-02-23 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of the Second European Conference on Computational Learning Theory (EuroCOLT '95), held in Barcelona, Spain in March 1995. The book contains full versions of the 28 papers accepted for presentation at the conference as well as three invited papers. All relevant topics in fundamental studies of computational aspects of artificial and natural learning systems and machine learning are covered; in particular artificial and biological neural networks, genetic and evolutionary algorithms, robotics, pattern recognition, inductive logic programming, decision theory, Bayesian/MDL estimation, statistical physics, and cryptography are addressed.

Book Computational Learning Theory

Download or read book Computational Learning Theory written by David Helmbold and published by Springer Science & Business Media. This book was released on 2001-07-04 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.

Book Proceedings of the Annual ACM Conference on Computational Learning Theory 7 July 12th 15th 1994 New Brunswick New Jersey

Download or read book Proceedings of the Annual ACM Conference on Computational Learning Theory 7 July 12th 15th 1994 New Brunswick New Jersey written by and published by . This book was released on 1994 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Language and Automata Theory and Applications

Download or read book Language and Automata Theory and Applications written by Adrian Horia Dediu and published by Springer Science & Business Media. This book was released on 2009-03-09 with total page 766 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Language and Automata Theory and Applications, LATA 2009, held in Tarragona, Spain, in April 2009. The 58 revised full papers presented together with 3 invited lectures and two tutorials were carefully reviewed and selected from 121 submissions. The papers address all the various issues related to automata theory and formal languages.

Book Writers in the Secret Garden

Download or read book Writers in the Secret Garden written by Cecilia Aragon and published by MIT Press. This book was released on 2019-08-20 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth examination of the novel ways young people support and learn from each other though participation in online fanfiction communities. Over the past twenty years, amateur fanfiction writers have published an astonishing amount of fiction in online repositories. More than 1.5 million enthusiastic fanfiction writers—primarily young people in their teens and twenties—have contributed nearly seven million stories and more than 176 million reviews to a single online site, Fanfiction.net. In this book, Cecilia Aragon and Katie Davis provide an in-depth examination of fanfiction writers and fanfiction repositories, finding that these sites are not shallow agglomerations and regurgitations of pop culture but rather online spaces for sophisticated and informal learning. Through their participation in online fanfiction communities, young people find ways to support and learn from one another. Aragon and Davis term this novel system of interactive advice and instruction distributed mentoring, and describe its seven attributes, each of which is supported by an aspect of networked technologies: aggregation, accretion, acceleration, abundance, availability, asynchronicity, and affect. Employing an innovative combination of qualitative and quantitative analyses, they provide an in-depth ethnography, reporting on a nine-month study of three fanfiction sites, and offer a quantitative analysis of lexical diversity in the 61.5 billion words on the Fanfiction.net site. Going beyond fandom, Aragon and Davis consider how distributed mentoring could improve not only other online learning platforms but also formal writing instruction in schools.

Book Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory

Download or read book Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory written by ACM Conference on Computational Learning Theory and published by . This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Proceedings of the Fifth Annual Acm Workshop on Computational Learning Theory

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:

Book Algorithmic Learning Theory

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.

Book Advanced Lectures on Machine Learning

Download or read book Advanced Lectures on Machine Learning written by Shahar Mendelson and published by Springer. This book was released on 2003-07-01 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11–22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at http://mlg. anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will ?nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.

Book Computational Learning Theory

Download or read book Computational Learning Theory written by Martin Anthony and published by . This book was released on 1992 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational learning theory is a subject which has been advancing rapidly in the last few years. The authors concentrate on the probably approximately correct model of learning, and gradually develop the ideas of efficiency considerations. Finally, applications of the theory to artificial neural networks are considered. Many exercises are included throughout, and the list of references is extensive. This volume is relatively self contained as the necessary background material from logic, probability and complexity theory is included. It will therefore form an introduction to the theory of computational learning, suitable for a broad spectrum of graduate students from theoretical computer science and mathematics.