SYMPOSIUM ON LEARNING AND DATA SCIENCE
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 of this conference 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.
SLDS2009 presented the most noteworthy foundations of these domains from the past century.
POST-SYMPOSIUM SLDS2009 BOOK : "STATISTICAL LEARNING AND DATA SCIENCE"
The SLDS2012 symposium focuses on contemporary and future theoretical problems as well as on efficient practical solutions for applied domains which involve Data Analysis, Data Mining, Machine Learning and Statistical Learning contributions.
This Symposium is important for researchers and all who want to keep abreast of future developments in data handling and of the consequent results that can be imagined in various applied domains.
The focus of the Symposium includes, but is not limited to, the following themes:
Knowledge Discovery by Modeling, Performance Guaranteed Machine Learning Algorithms, Challenges in Text Mining, Social Networks, Complex/Symbolic Data Analysis, Geometric Data Analysis towards Sociology Challenges, Visual Decision Aids, Challenges in Astronomy Data Mining, Mining and Learning for Neuroscience Challenges, Mining and Learning for Omics Challenges, Open Data