Great progress has been made in the past 20 years in Machine Learning and Statistical Learning, Data Analysis and Data Mining. From the statistical analysis of data to data mining, from machine learning to knowledge discovery, the development of data exploration and modeling has overcome numerous challenges and has benefited greatly from varied, often overlapping, paradigms.
By uniting specialists with different expertise and from different disciplines, the objectives are to compare approaches to data, to deepen understanding of different methodologies, and to focus on the Grand Challenges that must be addressed in the coming years.
The objectives of this Symposium will be achieved through presentations on core and also innovative themes. The precise topics will be chosen by the invited speakers, who have been the founders or the developers of their selected theme areas in recent years. The presentation and discussant format chosen will facilitate discussion with all of the participants.
This Symposium is important for researchers and all who want to keep abreast of the latest developments in data handling. In addition there isa competition specifically addressed to young researchers.
The focus of the Symposium includes, but is not limited to, the following themes:
Inductive and Transductive Inference, Graphical Models, Intelligent Data Analysis, Analysis of Massive, High Dimensional Data Stores and Data Streams, Knowledge Discovery from Textual and Multimedia Data, and Innovative Applications.
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