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.
4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. Proceedings
4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. Proceedings
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.
This book constitutes the refereed proceedings of the Third International Conference on Discovery Science, DS 2000, held in Kyoto, Japan in December 2000. The 15 revised full papers presented together with three invited contributions and 22 posters were carefully reviewed and selected from 48 submissions. Among the topics and areas addressed in their relation to discovery science are inference, algorithmic learning, heuristic search, database management, data mining, networking, inductive logic programming, information agents, information retrieval, visualization, etc.
This volume contains 3 invited papers, 15 regular papers, and 22 poster papers that were selected for presentation at the Third International Conference on Discovery Science (DS 2000), which was held 4-6 December 2000 in Kyoto. The Program Committee selected the contributed papers from 48 submissions. Three distinguished researchers accepted our invitation to present talks: J- frey D. Ullman (Stanford University), Joseph Y. Halpern (Cornell University), and Masami Hagiya (University of Tokyo). The Program Committee would like to thank all those who submitted papers for consideration and the invited speakers. I would like to thank the Program Committee members, the Local Arrangements Committee members, and the Steering Committee members for their splendid and hard work. Finally, special thanks go to the PC Assistant Shoko Suzuki for her assistance in the development of web pages and the preparation of these proceedings. September 2000 Shinichi Morishita Organization Discovery Science 2000 is organized as part of the activities of the Discovery Science Project sponsored by Grant-in-Aid for Scienti?c Research in the Priority Area from the Ministry of Education, Science, Sports and Culture (MESSC) of Japan, in cooperation with the Japanese Society for Arti?cial Intelligence, and with SIG of Data Mining, Japan Society for Software Science and Technology.
This book constitutes the refereed proceedings of the First International Conference on Discovery Science, DS'98, held in Fukuoka, Japan, in December 1998. The volume presents 28 revised full papers selected from a total of 76 submissions. Also included are five invited contributions and 34 selected poster presentations. The ultimate goal of DS'98 and this volume is to establish discovery science as a new field of research and development. The papers presented relate discovery science to areas as formal logic, knowledge processing, machine learning, automated deduction, searching, neural networks, database management, information retrieval, intelligent network agents, visualization, knowledge discovery, data mining, information extraction, etc.
This book constitutes the refereed proceedings of the Second International Conference on Discovery Science, DS'99, held in Tokyo, Japan, in December 1999. The 26 revised full papers presented together with 2 invited contributions and 25 poster presentations were carefully reviewed and selected from a total of 74 submissions. The following topics are covered in their relation to discovery science: logic, inference, algorithmic learning, heuristic search, database management, data mining, networking, inductive logic programming, abductive reasoning, machine learning, constructive programming, intelligent agents, statistical methods, visualization, HCI, etc.
4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. Proceedings
4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. Proceedings
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.
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.
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