Download or read book Proceedings of the Twelfth Annual ACM SIAM Symposium on Discrete Algorithms written by SIAM Activity Group on Discrete Mathematics and published by SIAM. This book was released on 2001-01-01 with total page 962 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains 130 papers, which were selected based on originality, technical contribution, and relevance. Although the papers were not formally refereed, every attempt was made to verify the main claims. It is expected that most will appear in more complete form in scientific journals. The proceedings also includes the paper presented by invited plenary speaker Ronald Graham, as well as a portion of the papers presented by invited plenary speakers Udi Manber and Christos Papadimitriou.
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:
Download or read book Proceedings of the Annual Conference on Computational Learning Theory written by and published by . This book was released on 1999 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Boosting written by Robert E. Schapire and published by MIT Press. This book was released on 2014-01-10 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
Download or read book Advances in Learning Theory written by Johan A. K. Suykens and published by IOS Press. This book was released on 2003 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics.
Download or read book Learning Theory written by Peter Auer and published by Springer Science & Business Media. This book was released on 2005-06-20 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th Annual Conference on Learning Theory, COLT 2005, held in Bertinoro, Italy in June 2005. The 45 revised full papers together with three articles on open problems presented were carefully reviewed and selected from a total of 120 submissions. The papers are organized in topical sections on: learning to rank, boosting, unlabeled data, multiclass classification, online learning, support vector machines, kernels and embeddings, inductive inference, unsupervised learning, generalization bounds, query learning, attribute efficiency, compression schemes, economics and game theory, separation results for learning models, and survey and prospects on open problems.
Download or read book Algorithmic Learning Theory written by Marcus Hutter and published by Springer Science & Business Media. This book was released on 2010-09-27 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at the 21st International Conf- ence on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6–8, 2010. The conference was co-located with the 13th - ternational Conference on Discovery Science (DS 2010) and with the Machine Learning Summer School, which was held just before ALT 2010. The tech- cal program of ALT 2010, contained 26 papers selected from 44 submissions and ?ve invited talks. The invited talks were presented in joint sessions of both conferences. ALT 2010 was dedicated to the theoretical foundations of machine learning and took place on the campus of the Australian National University, Canberra, Australia. ALT provides a forum for high-quality talks with a strong theore- cal background and scienti?c interchange in areas such as inductive inference, universal prediction, teaching models, grammatical inference, formal languages, inductive logic programming, query learning, complexity of learning, on-line learning and relative loss bounds, semi-supervised and unsupervised learning, clustering,activelearning,statisticallearning,supportvectormachines,Vapnik- Chervonenkisdimension,probablyapproximatelycorrectlearning,Bayesianand causal networks, boosting and bagging, information-based methods, minimum descriptionlength,Kolmogorovcomplexity,kernels,graphlearning,decisiontree methods, Markov decision processes, reinforcement learning, and real-world - plications of algorithmic learning theory. DS 2010 was the 13th International Conference on Discovery Science and focused on the development and analysis of methods for intelligent data an- ysis, knowledge discovery and machine learning, as well as their application to scienti?c knowledge discovery. As is the tradition, it was co-located and held in parallel with Algorithmic Learning Theory.
Download or read book Algorithmic Learning Theory written by José L. Balcázar and published by Springer Science & Business Media. This book was released on 2006-09-27 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006. The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning.
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 ECAI 2023 written by K. Gal and published by IOS Press. This book was released on 2023-10-18 with total page 3328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
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.
Download or read book Machine Learning Proceedings 1995 written by Armand Prieditis and published by Morgan Kaufmann. This book was released on 2014-06-28 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Proceedings 1995
Download or read book Proceedings of the 35th Annual ACM Symposium on the Theory of Computing written by and published by . This book was released on 2003 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Algorithmic Learning Theory written by Naoki Abe and published by Springer. This book was released on 2003-06-30 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at the 12th Annual Conference on Algorithmic Learning Theory (ALT 2001), which was held in Washington DC, USA, during November 25–28, 2001. The main objective of the conference is to provide an inter-disciplinary forum for the discussion of theoretical foundations of machine learning, as well as their relevance to practical applications. The conference was co-located with the Fourth International Conference on Discovery Science (DS 2001). The volume includes 21 contributed papers. These papers were selected by the program committee from 42 submissions based on clarity, signi?cance, o- ginality, and relevance to theory and practice of machine learning. Additionally, the volume contains the invited talks of ALT 2001 presented by Dana Angluin of Yale University, USA, Paul R. Cohen of the University of Massachusetts at Amherst, USA, and the joint invited talk for ALT 2001 and DS 2001 presented by Setsuo Arikawa of Kyushu University, Japan. Furthermore, this volume includes abstracts of the invited talks for DS 2001 presented by Lindley Darden and Ben Shneiderman both of the University of Maryland at College Park, USA. The complete versions of these papers are published in the DS 2001 proceedings (Lecture Notes in Arti?cial Intelligence Vol. 2226).
Download or read book Proceedings of the Twelfth Annual ACM Conference on Computational Learning Theory written by and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory written by and published by . This book was released on 1994 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Foundations of Rational Agency written by Michael Wooldridge and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume represents an advanced, comprehensive state-of-the-art survey of the field of rational agency as it stands today. It covers the philosophical foundations of rational agency, logical and decision-theoretic approaches to rational agency, multi-agent aspects of rational agency and a number of approaches to programming rational agents. It will be of interest to researchers in logic, mainstream computer science, the philosophy of rational action and agency, and economics.
