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This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning.
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
This book constitutes revised selected papers from the workshops collocated with the SEFM 2014 conference on Software Engineering and Formal Methods, held in Grenoble, France, in September 2014. The 26 papers included in this volume were carefully reviewed and selected from 49 submissions. They are from the following workshops: the 1st Workshop on Human-Oriented Formal Methods - From Readability to Automation, HOFM 2014, the 3rd International Symposium on Modelling and Knowledge Management Applications - Systems and Domains, MoKMaSD 2014, the 8th International Workshop on Foundations and Techniques for Open Source Software Certification, Open Cert 2014, the 1st Workshop on Safety and Formal Methods, SaFoMe 2014 and the 4th Workshop on Formal Methods in the Development of Software, WS-FMDS 2014.
This book constitutes the refereed conference proceedings of the 13th International Conference on Intelligent Data Analysis, which was held in October/November 2014 in Leuven, Belgium. The 33 revised full papers together with 3 invited papers were carefully reviewed and selected from 70 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Annotation. This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2010, held in Barcelona, Spain, in September 2010. The 120 revised full papers presented in three volumes, together with 12 demos (out of 24 submitted demos), were carefully reviewed and selected from 658 paper submissions. In addition, 7 ML and 7 DM papers were distinguished by the program chairs on the basis of their exceptional scientific quality and high impact on the field. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. A topic widely explored from both ML and DM perspectives was graphs, with motivations ranging from molecular chemistry to social networks.
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This book constitutes the refereed proceedings of the 7th International Conference on Intelligent Data Analysis, IDA 2007, held in Ljubljana, Slovenia. The 33 revised papers were carefully reviewed and selected from almost 100 submissions. The book covers all current aspects of this interdisciplinary field, including statistics, machine learning, data mining, classification and pattern recognition, clustering, applications, modeling, and interactive dynamic data visualization.
This book constitutes the conference proceedings of the 16th International Symposium on Intelligent Data Analysis, which was held in October 2017 in London, UK. The 28 full papers presented in this book were carefully reviewed and selected from 66 submissions. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. IDA solicits papers on all aspects of intelligent data analysis, including papers on intelligent support for modelling and analyzing data from complex, dynamical systems.