Machine Learning Ecml 2001

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Machine Learning: ECML 2001

Author : Luc de Raedt
Publisher : Springer
ISBN 13 : 3540447954
Total Pages : 635 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Machine Learning: ECML 2001 by : Luc de Raedt

Download or read book Machine Learning: ECML 2001 written by Luc de Raedt and published by Springer. This book was released on 2003-06-30 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th European Conference on Machine Learning, ECML 2001, held in Freiburg, Germany, in September 2001. The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equation discovery, inductive logic programming, text categorization, agent learning, backpropagation, reinforcement learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.

Machine Learning: ECML 2001

Author : Luc de Raedt
Publisher : Springer
ISBN 13 : 9783540425366
Total Pages : 620 pages
Book Rating : 4.4/5 (253 download)

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Book Synopsis Machine Learning: ECML 2001 by : Luc de Raedt

Download or read book Machine Learning: ECML 2001 written by Luc de Raedt and published by Springer. This book was released on 2001-08-23 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th European Conference on Machine Learning, ECML 2001, held in Freiburg, Germany, in September 2001. The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equation discovery, inductive logic programming, text categorization, agent learning, backpropagation, reinforcement learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.

Machine Learning

Author : Raedt
Publisher :
ISBN 13 : 9783662205983
Total Pages : pages
Book Rating : 4.2/5 (59 download)

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Book Synopsis Machine Learning by : Raedt

Download or read book Machine Learning written by Raedt and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning: ECML 2002

Author : Tapio Elomaa
Publisher : Springer
ISBN 13 : 3540367551
Total Pages : 548 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Machine Learning: ECML 2002 by : Tapio Elomaa

Download or read book Machine Learning: ECML 2002 written by Tapio Elomaa and published by Springer. This book was released on 2002-01-01 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002. The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.

Machine Learning: ECML 2001

Author : Luc de Raedt
Publisher : Springer
ISBN 13 : 9783540447955
Total Pages : 0 pages
Book Rating : 4.4/5 (479 download)

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Book Synopsis Machine Learning: ECML 2001 by : Luc de Raedt

Download or read book Machine Learning: ECML 2001 written by Luc de Raedt and published by Springer. This book was released on 2003-06-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th European Conference on Machine Learning, ECML 2001, held in Freiburg, Germany, in September 2001. The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equation discovery, inductive logic programming, text categorization, agent learning, backpropagation, reinforcement learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.

Machine Learning: ECML 2004

Author : Jean-Francois Boulicaut
Publisher : Springer
ISBN 13 : 3540301151
Total Pages : 597 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Machine Learning: ECML 2004 by : Jean-Francois Boulicaut

Download or read book Machine Learning: ECML 2004 written by Jean-Francois Boulicaut and published by Springer. This book was released on 2004-11-05 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings of ECML/PKDD 2004 are published in two separate, albeit - tertwined,volumes:theProceedingsofthe 15thEuropeanConferenceonMac- ne Learning (LNAI 3201) and the Proceedings of the 8th European Conferences on Principles and Practice of Knowledge Discovery in Databases (LNAI 3202). The two conferences were co-located in Pisa, Tuscany, Italy during September 20–24, 2004. It was the fourth time in a row that ECML and PKDD were co-located. - ter the successful co-locations in Freiburg (2001), Helsinki (2002), and Cavtat- Dubrovnik (2003), it became clear that researchersstrongly supported the or- nization of a major scienti?c event about machine learning and data mining in Europe. We are happy to provide some statistics about the conferences. 581 di?erent papers were submitted to ECML/PKDD (about a 75% increase over 2003); 280 weresubmittedtoECML2004only,194weresubmittedtoPKDD2004only,and 107weresubmitted to both.Aroundhalfofthe authorsforsubmitted papersare from outside Europe, which is a clear indicator of the increasing attractiveness of ECML/PKDD. The Program Committee members were deeply involved in what turned out to be a highly competitive selection process. We assigned each paper to 3 - viewers, deciding on the appropriate PC for papers submitted to both ECML and PKDD. As a result, ECML PC members reviewed 312 papers and PKDD PC members reviewed 269 papers. We accepted for publication regular papers (45 for ECML 2004 and 39 for PKDD 2004) and short papers that were as- ciated with poster presentations (6 for ECML 2004 and 9 for PKDD 2004). The globalacceptance ratewas14.5%for regular papers(17% if we include the short papers).

Machine Learning: ECML 2003

Author : Nada Lavrač
Publisher : Springer Science & Business Media
ISBN 13 : 3540201211
Total Pages : 521 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Machine Learning: ECML 2003 by : Nada Lavrač

Download or read book Machine Learning: ECML 2003 written by Nada Lavrač and published by Springer Science & Business Media. This book was released on 2003-09-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th European Conference on Machine Learning, ECML 2003, held in Cavtat-Dubrovnik, Croatia in September 2003 in conjunction with PKDD 2003. The 40 revised full papers presented together with 4 invited contributions were carefully reviewed and, together with another 40 ones for PKDD 2003, selected from a total of 332 submissions. The papers address all current issues in machine learning including support vector machine, inductive inference, feature selection algorithms, reinforcement learning, preference learning, probabilistic grammatical inference, decision tree learning, clustering, classification, agent learning, Markov networks, boosting, statistical parsing, Bayesian learning, supervised learning, and multi-instance learning.

Machine Learning: ECML 2007

Author : Joost N. Kok
Publisher : Springer
ISBN 13 : 3540749586
Total Pages : 812 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Machine Learning: ECML 2007 by : Joost N. Kok

Download or read book Machine Learning: ECML 2007 written by Joost N. Kok and published by Springer. This book was released on 2007-09-08 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th European Conference on Machine Learning, ECML 2007, held in Warsaw, Poland, September 2007, jointly with PKDD 2007. The 41 revised full papers and 37 revised short papers presented together with abstracts of four invited talks were carefully reviewed and selected from 592 abstracts submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.

Machine Learning: ECML 2006

Author : Johannes Fürnkranz
Publisher : Springer Science & Business Media
ISBN 13 : 354045375X
Total Pages : 873 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Machine Learning: ECML 2006 by : Johannes Fürnkranz

Download or read book Machine Learning: ECML 2006 written by Johannes Fürnkranz and published by Springer Science & Business Media. This book was released on 2006-09-19 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held, jointly with PKDD 2006. The book presents 46 revised full papers and 36 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers present a wealth of new results in the area and address all current issues in machine learning.

Machine Learning: ECML 2005

Author : João Gama
Publisher : Springer Science & Business Media
ISBN 13 : 3540292438
Total Pages : 784 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Machine Learning: ECML 2005 by : João Gama

Download or read book Machine Learning: ECML 2005 written by João Gama and published by Springer Science & Business Media. This book was released on 2005-09-22 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.

Machine Learning and Knowledge Discovery in Databases

Author : José L. Balcázar
Publisher : Springer
ISBN 13 : 3642158838
Total Pages : 538 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : José L. Balcázar

Download or read book Machine Learning and Knowledge Discovery in Databases written by José L. Balcázar and published by Springer. This book was released on 2010-08-17 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2010, was held in Barcelona, September 20–24, 2010, consolidating the long junction between the European Conference on Machine Learning (of which the ?rst instance as European wo- shop dates back to 1986) and Principles and Practice of Knowledge Discovery in Data Bases (of which the ?rst instance dates back to 1997). Since the two conferences were ?rst collocated in 2001, both machine learning and data m- ing communities have realized how each discipline bene?ts from the advances, and participates to de?ning the challenges, of the sister discipline. Accordingly, a single ECML PKDD Steering Committee gathering senior members of both communities was appointed in 2008. In 2010, as in previous years, ECML PKDD lasted from Monday to F- day. It involved six plenary invited talks, by Christos Faloutsos, Jiawei Han, Hod Lipson, Leslie Pack Kaelbling, Tomaso Poggio, and Jur ̈ gen Schmidhuber, respectively. Monday and Friday were devoted to workshops and tutorials, or- nized and selected by Colin de la Higuera and Gemma Garriga.Continuing from ECML PKDD 2009, an industrial session managed by Taneli Mielikainen and Hugo Zaragoza welcomed distinguished speakers from the ML and DM ind- try: Rakesh Agrawal, Mayank Bawa, Ignasi Belda, Michael Berthold, Jos ́eLuis Fl ́ orez, ThoreGraepel, andAlejandroJaimes.Theconferencealsofeaturedad- coverychallenge, organizedbyAndr ́ asBenczur ́, CarlosCastillo, Zolt ́ anGyon ̈ gyi, and Julien Masan' es.

Machine Learning, ECML- ...

Author :
Publisher :
ISBN 13 :
Total Pages : 614 pages
Book Rating : 4.3/5 (91 download)

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Download or read book Machine Learning, ECML- ... written by and published by . This book was released on 2004 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning: ECML-98

Author : Claire Nedellec
Publisher : Lecture Notes in Artificial Intelligence
ISBN 13 :
Total Pages : 440 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Machine Learning: ECML-98 by : Claire Nedellec

Download or read book Machine Learning: ECML-98 written by Claire Nedellec and published by Lecture Notes in Artificial Intelligence. This book was released on 1998-04-08 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th European Conference on Machine Learning, ECML-98, held in Chemnitz, Germany, in April 1998. The book presents 21 revised full papers and 25 short papers reporting on work in progress together with two invited contributions; the papers were selected from a total of 100 submissions. The book is divided in sections on applications of ML, Bayesian networks, feature selection, decision trees, support vector learning, multiple models for classification, inductive logic programming, relational learning, instance-based learning, clustering, genetic algorithms, reinforcement learning and neural networks.

Artificial General Intelligence

Author : Ben Goertzel
Publisher : Springer Science & Business Media
ISBN 13 : 3540686770
Total Pages : 518 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Artificial General Intelligence by : Ben Goertzel

Download or read book Artificial General Intelligence written by Ben Goertzel and published by Springer Science & Business Media. This book was released on 2007-01-17 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Only a small community has concentratedon general intelligence. No one has tried to make a thinking machine . . . The bottom line is that we really haven’t progressed too far toward a truly intelligent machine. We have collections of dumb specialists in small domains; the true majesty of general intelligence still awaits our attack. . . . We have got to get back to the deepest questions of AI and general intelligence. . . ” –MarvinMinsky as interviewed in Hal’s Legacy, edited by David Stork, 2000. Our goal in creating this edited volume has been to ?ll an apparent gap in the scienti?c literature, by providing a coherent presentation of a body of contemporary research that, in spite of its integral importance, has hitherto kept a very low pro?le within the scienti?c and intellectual community. This body of work has not been given a name before; in this book we christen it “Arti?cial General Intelligence” (AGI). What distinguishes AGI work from run-of-the-mill “arti?cial intelligence” research is that it is explicitly focused on engineering general intelligence in the short term. We have been active researchers in the AGI ?eld for many years, and it has been a pleasure to gather together papers from our colleagues working on related ideas from their own perspectives. In the Introduction we give a conceptual overview of the AGI ?eld, and also summarize and interrelate the key ideas of the papers in the subsequent chapters.

Recent Advances in Artificial Intelligence Research and Development

Author : Jordi Vitrià
Publisher : IOS Press
ISBN 13 : 9781586034665
Total Pages : 468 pages
Book Rating : 4.0/5 (346 download)

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Book Synopsis Recent Advances in Artificial Intelligence Research and Development by : Jordi Vitrià

Download or read book Recent Advances in Artificial Intelligence Research and Development written by Jordi Vitrià and published by IOS Press. This book was released on 2004 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) is a scientific field of longstanding tradition, with origins in the early years of computer science. Today AI has reached a level of maturity that allows us to build highly sophisticated systems which perform very different tasks. Nevertheless, its evolution has opened up a number of new problems, ranging from specific algorithms to system integration, which remain elusive and assure a long life for this research field. Research progress in this area is today an international challenge that must be supported by world-class meetings and organizations, but in spite of this fact, there is also an objective need for meetings and organizations that support and disseminate research at other levels. This book focuses on new and original research on Artificial Intelligence.

Innovations in Machine Learning

Author : Dawn E. Holmes
Publisher : Springer
ISBN 13 : 3540334866
Total Pages : 285 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Innovations in Machine Learning by : Dawn E. Holmes

Download or read book Innovations in Machine Learning written by Dawn E. Holmes and published by Springer. This book was released on 2006-02-28 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.

Universal Artificial Intelligence

Author : Marcus Hutter
Publisher : Springer Science & Business Media
ISBN 13 : 3540268774
Total Pages : 294 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Universal Artificial Intelligence by : Marcus Hutter

Download or read book Universal Artificial Intelligence written by Marcus Hutter and published by Springer Science & Business Media. This book was released on 2005-12-29 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personal motivation. The dream of creating artificial devices that reach or outperform human inteUigence is an old one. It is also one of the dreams of my youth, which have never left me. What makes this challenge so interesting? A solution would have enormous implications on our society, and there are reasons to believe that the AI problem can be solved in my expected lifetime. So, it's worth sticking to it for a lifetime, even if it takes 30 years or so to reap the benefits. The AI problem. The science of artificial intelligence (AI) may be defined as the construction of intelligent systems and their analysis. A natural definition of a system is anything that has an input and an output stream. Intelligence is more complicated. It can have many faces like creativity, solving prob lems, pattern recognition, classification, learning, induction, deduction, build ing analogies, optimization, surviving in an environment, language processing, and knowledge. A formal definition incorporating every aspect of intelligence, however, seems difficult. Most, if not all known facets of intelligence can be formulated as goal driven or, more precisely, as maximizing some utility func tion. It is, therefore, sufficient to study goal-driven AI; e. g. the (biological) goal of animals and humans is to survive and spread. The goal of AI systems should be to be useful to humans.