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Proceedings Of The Annual Acm Conference On Computational Learning Theory
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Book Synopsis Proceedings of the ... Annual ACM Conference on Computational Learning Theory by :
Download or read book Proceedings of the ... Annual ACM Conference on Computational Learning Theory written by and published by . This book was released on 1999 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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.
Book Synopsis Learning Theory by : Hans Ulrich Simon
Download or read book Learning Theory written by Hans Ulrich Simon and published by Springer. This book was released on 2006-09-29 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA, June 2006. The book presents 43 revised full papers together with 2 articles on open problems and 3 invited lectures. The papers cover a wide range of topics including clustering, un- and semi-supervised learning, statistical learning theory, regularized learning and kernel methods, query learning and teaching, inductive inference, and more.
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:
Download or read book Learning Theory written by Peter Auer and published by Springer. This book was released on 2005-06-28 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains papers presented at the Eighteenth Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Bertinoro, Italy from June 27 to 30, 2005. The technical program contained 45 papers selected from 120 submissions, 3 open problems selected from among 5 contributed, and 2 invited lectures. The invited lectures were given by Sergiu Hart on “Uncoupled Dynamics and Nash Equilibrium”, and by Satinder Singh on “Rethinking State, Action, and Reward in Reinforcement Learning”. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. The student selected this year was Hadi Salmasian for the paper titled “The Spectral Method for General Mixture Models” co-authored with Ravindran Kannan and Santosh Vempala. The number of papers submitted to COLT this year was exceptionally high. In addition to the classical COLT topics, we found an increase in the number of submissions related to novel classi?cation scenarios such as ranking. This - crease re?ects a healthy shift towards more structured classi?cation problems, which are becoming increasingly relevant to practitioners.
Author :ACM Special Interest Group for Automata and Computability Theory Publisher :Morgan Kaufmann ISBN 13 :9781558601468 Total Pages :408 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 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.
Book Synopsis Computational Learning Theory by : Jyrki Kivinen
Download or read book Computational Learning Theory written by Jyrki Kivinen and published by Springer Science & Business Media. This book was released on 2002-06-26 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is tailored for students and professionals as well as novices from other fields to mass spectrometry. It will guide them from the basics to the successful application of mass spectrometry in their daily research. Starting from the very principles of gas-phase ion chemistry and isotopic properties, it leads through the design of mass analyzers and ionization methods in use to mass spectral interpretation and coupling techniques. Step by step the readers will learn how mass spectrometry works and what it can do as a powerful tool in their hands. The book comprises a balanced mixture of practice-oriented information and theoretical background. The clear layout, a wealth of high-quality figures and a database of exercises and solutions, accessible via the publisher's web site, support teaching and learning.
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 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 2001-07-04 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.
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.
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.
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.
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.
Book Synopsis Proceedings of the ... Annual ACM Conference on Computational Learning Theory by :
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:
Book Synopsis Photonics Applications in Astronomy, Communications, Industry, and High-energy Physics Experiments 2016 by : IEEE-SPIE Joint Symposium Wilga
Download or read book Photonics Applications in Astronomy, Communications, Industry, and High-energy Physics Experiments 2016 written by IEEE-SPIE Joint Symposium Wilga and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithmic Learning Theory by : Arun K. Sharma
Download or read book Algorithmic Learning Theory written by Arun K. Sharma and published by Springer Science & Business Media. This book was released on 1996-10-09 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Algorithmic Learning Theory, ALT '96, held in Sydney, Australia, in October 1996. The 16 revised full papers presented were selected from 41 submissions; also included are eight short papers as well as four full length invited contributions by Ross Quinlan, Takeshi Shinohara, Leslie Valiant, and Paul Vitanyi, and an introduction by the volume editors. The book covers all areas related to algorithmic learning theory, ranging from theoretical foundations of machine learning to applications in several areas.