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Proceedings Of The Third Annual Workshop On Computational Learning Theory
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Author :ACM Special Interest Group for Automata and Computability Theory Publisher :Morgan Kaufmann ISBN 13 : Total Pages :408 pages Book Rating :4.:/5 (321 download)
Book Synopsis Proceedings of the Third Annual Workshop on Computational Learning Theory by : ACM Special Interest Group for Automata and Computability Theory
Download or read book Proceedings of the Third Annual Workshop on Computational Learning Theory written by ACM Special Interest Group for Automata and Computability Theory and published by Morgan Kaufmann. This book was released on 1990 with total page 408 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 :ACM Special Interest Group for Automata and Computability Theory Publisher :Morgan Kaufmann ISBN 13 :9781558601468 Total Pages :412 pages Book Rating :4.6/5 (14 download)
Book Synopsis Proceedings of the Third Annual Workshop on Computational Learning Theory by : ACM Special Interest Group for Automata and Computability Theory
Download or read book Proceedings of the Third Annual Workshop on Computational Learning Theory written by ACM Special Interest Group for Automata and Computability Theory and published by Morgan Kaufmann. This book was released on 1990 with total page 412 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.
Book Synopsis Computational Learning Theory by : Jyrki Kivinen
Download or read book Computational Learning Theory written by Jyrki Kivinen and published by Springer. This book was released on 2003-08-02 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th Annual Conference on Computational Learning Theory, COLT 2002, held in Sydney, Australia, in July 2002. The 26 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on statistical learning theory, online learning, inductive inference, PAC learning, boosting, and other learning paradigms.
Book Synopsis Learning Theory and Kernel Machines by : Bernhard Schoelkopf
Download or read book Learning Theory and Kernel Machines written by Bernhard Schoelkopf and published by Springer Science & Business Media. This book was released on 2003-08-11 with total page 761 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.
Book Synopsis Algorithmic Learning Theory by : Osamu Watanabe
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 372 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 Synopsis Learning Theory and Kernel Machines by : Bernhard Schölkopf
Download or read book Learning Theory and Kernel Machines written by Bernhard Schölkopf and published by Springer. This book was released on 2003-11-11 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.
Book Synopsis Computational Learning Theory by : David Helmbold
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 638 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.
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 404 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.
Book Synopsis Computational Learning Theory by : David Helmbold
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.
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 389 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.
Book Synopsis Computational Learning Theory by : Paul Vitanyi
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.
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
Book Synopsis Computational Learning Theory by : Conference on Computational Learning Theory
Download or read book Computational Learning Theory written by Conference on Computational Learning Theory and published by . This book was released on 2002 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Learning Theory by : Paul Fischer
Download or read book Computational Learning Theory written by Paul Fischer and published by Springer. This book was released on 2003-07-31 with total page 299 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.
Book Synopsis Algorithmic Learning Theory II by : Setsuo Arikawa
Download or read book Algorithmic Learning Theory II written by Setsuo Arikawa and published by IOS Press. This book was released on 1992 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithmic Learning Theory by : Klaus P. Jantke
Download or read book Algorithmic Learning Theory written by Klaus P. Jantke and published by Springer Science & Business Media. This book was released on 1993-10-20 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation This volume contains the papers that were presented at theThird Workshop onAlgorithmic Learning Theory, held in Tokyoin October 1992. In addition to 3invited papers, the volumecontains 19 papers accepted for presentation, selected from29 submitted extended abstracts. The ALT workshops have beenheld annually since 1990 and are organized and sponsored bythe Japanese Society for Artificial Intelligence. The mainobjective of these workshops is to provide an open forum fordiscussions and exchanges of ideasbetween researchers fromvarious backgrounds in this emerging, interdisciplinaryfield of learning theory. The volume is organized into partson learning via query, neural networks, inductive inference, analogical reasoning, and approximate learning.
Download or read book Learning Theory written by Nader Bshouty and published by Springer. This book was released on 2007-06-12 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th Annual Conference on Learning Theory, COLT 2007, held in San Diego, CA, USA in June 2007. It covers unsupervised, semisupervised and active learning, statistical learning theory, inductive inference, regularized learning, kernel methods, SVM, online and reinforcement learning, learning algorithms and limitations on learning, dimensionality reduction, as well as open problems.
