Algorithmic Learning Theory - ALT '92

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540573692
Total Pages : 276 pages
Book Rating : 4.5/5 (736 download)

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Book Synopsis Algorithmic Learning Theory - ALT '92 by : Shuji Doshita

Download or read book Algorithmic Learning Theory - ALT '92 written by Shuji Doshita and published by Springer Science & Business Media. This book was released on 1993-10-20 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers that were presented at the Third Workshop onAlgorithmic Learning Theory, held in Tokyo in October 1992. In addition to 3invited papers, the volume contains 19 papers accepted for presentation, selected from 29 submitted extended abstracts. The ALT workshops have been held annually since 1990 and are organized and sponsored by the Japanese Society for Artificial Intelligence. The main objective of these workshops is to provide an open forum for discussions and exchanges of ideasbetween researchers from various backgrounds in this emerging, interdisciplinary field of learning theory. The volume is organized into parts on learning via query, neural networks, inductive inference, analogical reasoning, and approximate learning.

Algorithmic Learning Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540585206
Total Pages : 600 pages
Book Rating : 4.5/5 (852 download)

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Book Synopsis Algorithmic Learning Theory by : Setsuo Arikawa

Download or read book Algorithmic Learning Theory written by Setsuo Arikawa and published by Springer Science & Business Media. This book was released on 1994-09-28 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Algorithmic Learning Theory

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Publisher : Springer
ISBN 13 : 3540497307
Total Pages : 450 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Algorithmic Learning Theory by : Michael M. Richter

Download or read book Algorithmic Learning Theory written by Michael M. Richter and published by Springer. This book was released on 2003-06-29 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains all the papers presented at the Ninth International Con- rence on Algorithmic Learning Theory (ALT’98), held at the European education centre Europ ̈aisches Bildungszentrum (ebz) Otzenhausen, Germany, October 8{ 10, 1998. The Conference was sponsored by the Japanese Society for Arti cial Intelligence (JSAI) and the University of Kaiserslautern. Thirty-four papers on all aspects of algorithmic learning theory and related areas were submitted, all electronically. Twenty-six papers were accepted by the program committee based on originality, quality, and relevance to the theory of machine learning. Additionally, three invited talks presented by Akira Maruoka of Tohoku University, Arun Sharma of the University of New South Wales, and Stefan Wrobel from GMD, respectively, were featured at the conference. We would like to express our sincere gratitude to our invited speakers for sharing with us their insights on new and exciting developments in their areas of research. This conference is the ninth in a series of annual meetings established in 1990. The ALT series focuses on all areas related to algorithmic learning theory including (but not limited to): the theory of machine learning, the design and analysis of learning algorithms, computational logic of/for machine discovery, inductive inference of recursive functions and recursively enumerable languages, learning via queries, learning by arti cial and biological neural networks, pattern recognition, learning by analogy, statistical learning, Bayesian/MDL estimation, inductive logic programming, robotics, application of learning to databases, and gene analyses.

Algorithmic Learning Theory

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Publisher :
ISBN 13 :
Total Pages : 364 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Algorithmic Learning Theory by :

Download or read book Algorithmic Learning Theory written by and published by . This book was released on 2000 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Learning Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540591191
Total Pages : 442 pages
Book Rating : 4.5/5 (911 download)

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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.

Algorithmic Learning Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540573708
Total Pages : 444 pages
Book Rating : 4.5/5 (737 download)

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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.

Algorithmic Learning Theory

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Publisher : Springer
ISBN 13 : 3540455833
Total Pages : 388 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Algorithmic Learning Theory by : Naoki Abe

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).

Computational Learning Theory and Natural Learning Systems: Making learning systems practical

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Publisher : MIT Press
ISBN 13 : 9780262571180
Total Pages : 440 pages
Book Rating : 4.5/5 (711 download)

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Book Synopsis Computational Learning Theory and Natural Learning Systems: Making learning systems practical by : Russell Greiner

Download or read book Computational Learning Theory and Natural Learning Systems: Making learning systems practical written by Russell Greiner and published by MIT Press. This book was released on 1994 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the fourth and final volume of papers from a series of workshops called "Computational Learning Theory and Ǹatural' Learning Systems." The purpose of the workshops was to explore the emerging intersection of theoretical learning research and natural learning systems. The workshops drew researchers from three historically distinct styles of learning research: computational learning theory, neural networks, and machine learning (a subfield of AI). Volume I of the series introduces the general focus of the workshops. Volume II looks at specific areas of interaction between theory and experiment. Volumes III and IV focus on key areas of learning systems that have developed recently. Volume III looks at the problem of "Selecting Good Models." The present volume, Volume IV, looks at ways of "Making Learning Systems Practical." The editors divide the twenty-one contributions into four sections. The first three cover critical problem areas: 1) scaling up from small problems to realistic ones with large input dimensions, 2) increasing efficiency and robustness of learning methods, and 3) developing strategies to obtain good generalization from limited or small data samples. The fourth section discusses examples of real-world learning systems. Contributors : Klaus Abraham-Fuchs, Yasuhiro Akiba, Hussein Almuallim, Arunava Banerjee, Sanjay Bhansali, Alvis Brazma, Gustavo Deco, David Garvin, Zoubin Ghahramani, Mostefa Golea, Russell Greiner, Mehdi T. Harandi, John G. Harris, Haym Hirsh, Michael I. Jordan, Shigeo Kaneda, Marjorie Klenin, Pat Langley, Yong Liu, Patrick M. Murphy, Ralph Neuneier, E.M. Oblow, Dragan Obradovic, Michael J. Pazzani, Barak A. Pearlmutter, Nageswara S.V. Rao, Peter Rayner, Stephanie Sage, Martin F. Schlang, Bernd Schurmann, Dale Schuurmans, Leon Shklar, V. Sundareswaran, Geoffrey Towell, Johann Uebler, Lucia M. Vaina, Takefumi Yamazaki, Anthony M. Zador.

Algorithmic Learning Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540618638
Total Pages : 362 pages
Book Rating : 4.6/5 (186 download)

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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.

Systems that Learn

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Publisher : MIT Press
ISBN 13 : 9780262100779
Total Pages : 346 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Systems that Learn by : Sanjay Jain

Download or read book Systems that Learn written by Sanjay Jain and published by MIT Press. This book was released on 1999 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to the concepts and techniques of formal learning theory is based on a number-theoretical approach to learning and uses the tools of recursive function theory to understand how learners come to an accurate view of reality.

Natural & Artificial Parallel Computation

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Publisher : SIAM
ISBN 13 : 9780898713572
Total Pages : 220 pages
Book Rating : 4.7/5 (135 download)

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Book Synopsis Natural & Artificial Parallel Computation by : David L. Waltz

Download or read book Natural & Artificial Parallel Computation written by David L. Waltz and published by SIAM. This book was released on 1996-01-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume begins with processing in biological organisms, moves through interactions between processing in biology and computer science, and ends with massively parallel computing. It contains articles by scientists exploring the modeling of biological systems on computers and computer designers interested in exploiting massive numbers of computing elements in parallel.

Algorithmic Learning Theory

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Publisher : Springer
ISBN 13 : 3540466509
Total Pages : 405 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Algorithmic Learning Theory by : José L. Balcázar

Download or read book Algorithmic Learning Theory written by José L. Balcázar and published by Springer. This book was released on 2006-10-05 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.

国立国会図書館所蔵科学技術関係欧文会議錄目錄

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Publisher :
ISBN 13 :
Total Pages : 1592 pages
Book Rating : 4.:/5 ( download)

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Book Synopsis 国立国会図書館所蔵科学技術関係欧文会議錄目錄 by : 国立国会図書館 (Japan)

Download or read book 国立国会図書館所蔵科学技術関係欧文会議錄目錄 written by 国立国会図書館 (Japan) and published by . This book was released on 1997 with total page 1592 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Grammatical Inference: Learning Syntax from Sentences

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540617785
Total Pages : 340 pages
Book Rating : 4.6/5 (177 download)

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Book Synopsis Grammatical Inference: Learning Syntax from Sentences by : Laurent Miclet

Download or read book Grammatical Inference: Learning Syntax from Sentences written by Laurent Miclet and published by Springer Science & Business Media. This book was released on 1996-09-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Colloquium on Grammatical Inference, ICGI-96, held in Montpellier, France, in September 1996. The 25 revised full papers contained in the book together with two invited key papers by Magerman and Knuutila were carefully selected for presentation at the conference. The papers are organized in sections on algebraic methods and algorithms, natural language and pattern recognition, inference and stochastic models, incremental methods and inductive logic programming, and operational issues.

Algorithmic Learning Theory

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Publisher : Springer
ISBN 13 : 3540409920
Total Pages : 351 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Algorithmic Learning Theory by : Hiroki Arimura

Download or read book Algorithmic Learning Theory written by Hiroki Arimura and published by Springer. This book was released on 2003-06-29 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Algorithmic Learning Theory, ALT 2000, held in Sydney, Australia in December 2000. The 22 revised full papers presented together with three invited papers were carefully reviewed and selected from 39 submissions. The papers are organized in topical sections on statistical learning, inductive logic programming, inductive inference, complexity, neural networks and other paradigms, support vector machines.

国立国会図書館所蔵科学技術関係欧文会議錄目錄

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Publisher :
ISBN 13 :
Total Pages : 1594 pages
Book Rating : 4.3/5 (91 download)

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Download or read book 国立国会図書館所蔵科学技術関係欧文会議錄目錄 written by and published by . This book was released on 1997 with total page 1594 pages. Available in PDF, EPUB and Kindle. Book excerpt:

FGCS '92

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Publisher : IOS Press
ISBN 13 : 9789051990997
Total Pages : 498 pages
Book Rating : 4.9/5 (99 download)

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Book Synopsis FGCS '92 by :

Download or read book FGCS '92 written by and published by IOS Press. This book was released on 1992 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: The FGCS project was introduced at a congerence in 1981 and commenced the following year. This volume contains the reports on the final phase of the project, showing how the research goals set were achieved.