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Discovery Science - 12th International Conference, DS 2009, Porto, Portugal, October 3-5, 2009 (Paperback, 2009 ed.)
Joao Gama, Vitor Santos Costa, Alipio Jorge, Pavel Brazdil
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R1,619
Discovery Miles 16 190
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Ships in 10 - 15 working days
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We are pleased to present the proceedings of the 12th International
Conference on Discovery Science (DS 2009), held in Porto, Portugal,
October 3-5, 2009. DS 2009 was collocated with ALT 2009, the 20th
International Conference on
AlgorithmicLearningTheory,continuingthesuccessfulDSconferenceseries.
DS 2009 provided an open forum for intensive discussions and the
exchange of new ideas among researchers working in the area of
discovery science. The scope of the conference included the
development and analysis of methods for automatic scienti?c
knowledge discovery, machine learning, intelligent data analysis,
and theory of learning, as well as their applications. We were
honored to have a very strong program. Acceptance for the
conference proceedings was very compe- tive. There were 92 papers
submitted, with the authors coming from roughly 20 di?erent
countries. All paperswere reviewedby three senior
researchersfollowed by an extensive discussion. The program
committee decided to accept 23 long papers (an acceptance rate of
25%) and 12 regular papers. The overall acc- tance rate was 38%.
The contributed papers cover a wide range of topics, from discovery
in general to data mining in particular. In addition to the
technicalpapers, we weredelighted to have?ve prestigious invited
speakers and two tutorials. Fernando Pereira, University of Penns-
vania, USA, presented new fundamental questions that should be
investigated in natural language processing in web mining. Hector
Ge?ner, from Pompeu Fabra University, Spain, discussed learning
methods for solving complete pl- ning domains.
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Knowledge Discovery in Databases: PKDD 2005 - 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings (Paperback, 2005 ed.)
Alipio Jorge, Luis Torgo, Pavel Brazdil, Rui Camacho, Joao Gama
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R3,343
Discovery Miles 33 430
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Ships in 10 - 15 working days
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The European Conference on Machine Learning (ECML) and the European
Conference on Principles and Practice of Knowledge Discovery in
Databases (PKDD) were jointly organized this year for the ?fth time
in a row, after some years of mutual independence before. After
Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004),
Porto received the 16th edition of ECML and the 9th PKDD in October
3-7. Having the two conferences together seems to be working well:
585 di?erent paper submissions were received for both events, which
maintains the high s- mission standard of last year. Of these, 335
were submitted to ECML only, 220 to PKDD only and 30 to both. Such
a high volume of scienti?c work required a tremendous e?ort from
Area Chairs, Program Committee members and some additional
reviewers. On average, PC members had 10 papers to evaluate, and
Area Chairs had 25 papers to decide upon. We managed to have 3
highly qua-
?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional
overall input from one of the Area Chairs. After the authors'
responses and the online discussions for many of the papers, we
arrived at the ?nal selection of 40 regular papers for ECML and 35
for PKDD. Besides these, 32 others were accepted as short papers
for ECML and 35 for PKDD. This represents a joint acceptance rate
of around 13% for regular papers and 25% overall. We thank all
involved for all the e?ort with reviewing and selection of papers.
Besidesthecoretechnicalprogram, ECMLandPKDDhad6invitedspeakers, 10
workshops, 8 tutorials and a Knowledge Discovery Challenge.
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Machine Learning: ECML 2005 - 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings (Paperback, 2005 ed.)
Joao Gama, Rui Camacho, Pavel Brazdil, Alipio Jorge, Luis Torgo
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R3,112
Discovery Miles 31 120
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Ships in 10 - 15 working days
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The European Conference on Machine Learning (ECML) and the European
Conference on Principles and Practice of Knowledge Discovery in
Databases (PKDD) were jointly organized this year for the ?fth time
in a row, after some years of mutual independence before. After
Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004),
Porto received the 16th edition of ECML and the 9th PKDD in October
3-7. Having the two conferences together seems to be working well:
585 di?erent paper submissions were received for both events, which
maintains the high s- mission standard of last year. Of these, 335
were submitted to ECML only, 220 to PKDD only and 30 to both. Such
a high volume of scienti?c work required a tremendous e?ort from
Area Chairs, Program Committee members and some additional
reviewers. On average, PC members had 10 papers to evaluate, and
Area Chairs had 25 papers to decide upon. We managed to have 3
highly qua-
?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional
overall input from one of the Area Chairs. After the authors'
responses and the online discussions for many of the papers, we
arrived at the ?nal selection of 40 regular papers for ECML and 35
for PKDD. Besides these, 32 others were accepted as short papers
for ECML and 35 for PKDD. This represents a joint acceptance rate
of around 13% for regular papers and 25% overall. We thank all
involved for all the e?ort with reviewing and selection of papers.
Besidesthecoretechnicalprogram, ECMLandPKDDhad6invitedspeakers, 10
workshops, 8 tutorials and a Knowledge Discovery Challenge.
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Progress in Artificial Intelligence: Knowledge Extraction, Multi-agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Porto, Portugal, December 17-20, 2001. Proceedings (Paperback, 2001 ed.)
Pavel Brazdil, Alipio Jorge
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R1,745
Discovery Miles 17 450
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 10th Portuguese Conference on Artificial Intelligence, EPTA 2001, held in Porto, Portugal, in December 2001. The 21 revised long papers and 18 revised short papers were carefully reviewed and selected from a total of 88 submissions. The papers are organized in topical sections on extraction of knowledge from databases, AI techniques for financial time series analysis, multi-agent systems, AI logics and logic programming, constraint satisfaction, and AI planning.
This open access book offers a comprehensive and thorough
introduction to almost all aspects of metalearning and automated
machine learning (AutoML), covering the basic concepts and
architecture, evaluation, datasets, hyperparameter optimization,
ensembles and workflows, and also how this knowledge can be used to
select, combine, compose, adapt and configure both algorithms and
models to yield faster and better solutions to data mining and data
science problems. It can thus help developers to develop systems
that can improve themselves through experience. As one of the
fastest-growing areas of research in machine learning, metalearning
studies principled methods to obtain efficient models and solutions
by adapting machine learning and data mining processes. This
adaptation usually exploits information from past experience on
other tasks and the adaptive processes can involve machine learning
approaches. As a related area to metalearning and a hot topic
currently, AutoML is concerned with automating the machine learning
processes. Metalearning and AutoML can help AI learn to control the
application of different learning methods and acquire new solutions
faster without unnecessary interventions from the user. This book
is a substantial update of the first edition published in 2009. It
includes 18 chapters, more than twice as much as the previous
version. This enabled the authors to cover the most relevant topics
in more depth and incorporate the overview of recent research in
the respective area. The book will be of interest to researchers
and graduate students in the areas of machine learning, data
mining, data science and artificial intelligence.
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