Algorithmic Learning Theory II
Author | : Setsuo Arikawa |
Publisher | : IOS Press |
Total Pages | : 324 |
Release | : 1992 |
Genre | : Algorithms |
ISBN | : 9784274076992 |
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Author | : Setsuo Arikawa |
Publisher | : IOS Press |
Total Pages | : 324 |
Release | : 1992 |
Genre | : Algorithms |
ISBN | : 9784274076992 |
Author | : Setsuo Arikawa |
Publisher | : |
Total Pages | : 364 |
Release | : 2014-01-15 |
Genre | : |
ISBN | : 9783662188941 |
Author | : Setsuo Arikawa |
Publisher | : Springer Science & Business Media |
Total Pages | : 600 |
Release | : 1994-09-28 |
Genre | : Computers |
ISBN | : 9783540585206 |
This volume presents the proceedings of the Fourth International Workshop on Analogical and Inductive Inference (AII '94) and the Fifth International Workshop on Algorithmic Learning Theory (ALT '94), held jointly at Reinhardsbrunn Castle, Germany in October 1994. (In future the AII and ALT workshops will be amalgamated and held under the single title of Algorithmic Learning Theory.) The book contains revised versions of 45 papers on all current aspects of computational learning theory; in particular, algorithmic learning, machine learning, analogical inference, inductive logic, case-based reasoning, and formal language learning are addressed.
Author | : Setsuo Arikawa |
Publisher | : Springer |
Total Pages | : 464 |
Release | : 1990 |
Genre | : Computers |
ISBN | : |
Author | : Shai Ben David |
Publisher | : Springer Science & Business Media |
Total Pages | : 519 |
Release | : 2004-09-23 |
Genre | : Computers |
ISBN | : 3540233563 |
Algorithmic learning theory is mathematics about computer programs which learn from experience. This involves considerable interaction between various mathematical disciplines including theory of computation, statistics, and c- binatorics. There is also considerable interaction with the practical, empirical ?elds of machine and statistical learning in which a principal aim is to predict, from past data about phenomena, useful features of future data from the same phenomena. The papers in this volume cover a broad range of topics of current research in the ?eld of algorithmic learning theory. We have divided the 29 technical, contributed papers in this volume into eight categories (corresponding to eight sessions) re?ecting this broad range. The categories featured are Inductive Inf- ence, Approximate Optimization Algorithms, Online Sequence Prediction, S- tistical Analysis of Unlabeled Data, PAC Learning & Boosting, Statistical - pervisedLearning,LogicBasedLearning,andQuery&ReinforcementLearning. Below we give a brief overview of the ?eld, placing each of these topics in the general context of the ?eld. Formal models of automated learning re?ect various facets of the wide range of activities that can be viewed as learning. A ?rst dichotomy is between viewing learning as an inde?nite process and viewing it as a ?nite activity with a de?ned termination. Inductive Inference models focus on inde?nite learning processes, requiring only eventual success of the learner to converge to a satisfactory conclusion.
Author | : Sanjay Jain |
Publisher | : Springer Science & Business Media |
Total Pages | : 502 |
Release | : 2005-09-26 |
Genre | : Computers |
ISBN | : 354029242X |
This book constitutes the refereed proceedings of the 16th International Conference on Algorithmic Learning Theory, ALT 2005, held in Singapore in October 2005. The 30 revised full papers presented together with 5 invited papers and an introduction by the editors were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on kernel-based learning, bayesian and statistical models, PAC-learning, query-learning, inductive inference, language learning, learning and logic, learning from expert advice, online learning, defensive forecasting, and teaching.
Author | : José L. Balcázar |
Publisher | : Springer Science & Business Media |
Total Pages | : 405 |
Release | : 2006-09-27 |
Genre | : Computers |
ISBN | : 3540466495 |
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.
Author | : Jyriki Kivinen |
Publisher | : Springer |
Total Pages | : 465 |
Release | : 2011-10-07 |
Genre | : Computers |
ISBN | : 3642244122 |
This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models.
Author | : Arun K. Sharma |
Publisher | : Springer Science & Business Media |
Total Pages | : 362 |
Release | : 1996-10-09 |
Genre | : Computers |
ISBN | : 9783540618638 |
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.
Author | : Marcus Hutter |
Publisher | : Springer Science & Business Media |
Total Pages | : 415 |
Release | : 2007-09-17 |
Genre | : Computers |
ISBN | : 3540752242 |
This book constitutes the refereed proceedings of the 18th International Conference on Algorithmic Learning Theory, ALT 2007, held in Sendai, Japan, October 1-4, 2007, co-located with the 10th International Conference on Discovery Science, DS 2007. The 25 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 50 submissions. They are dedicated to the theoretical foundations of machine learning.