Special Session at ESANN 2018 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges/Belgium, April 25-27 2017.
Machine Learning and Data Analysis in Astroinformatics
Organized by M. Biehl, K. Bunte (University of Groningen, The Netherlands), G. Longo (University of Naples, Italy), P. Tino (University of Birmingham, UK)
Important dates:
Submission of papers: 29 November 2017
Notification of acceptance: 31 January 2018
ESANN conference: 25 - 27 April 2018
The ever-growing amount of data which becomes available in many domains clearly requires the development of efficient methods for data mining and analysis. These challenges occur in a variety of areas including societal issues, business and fundamental scientific research.
Astronomy continuous to be at the forefront of this development: Modern observational techniques provide enormous amounts of data, which have to be processed efficiently. The development of methods for their reliable acquisition and analysis has immediate impact on other areas including commercial applications, data security, environmental monitoring etc.
This special session is meant to attract researchers who develop, investigate or apply methods of neural networks, machine learning and data analysis in the context of astronomical data.
Potential topics include, but are not limited to:
- big data mining in astronomy
- the processing of astronomical images
- filtering techniques for streams of astronomical data
- outlier and novelty detection in observational data
- classification or clustering of celestial objects
- simulation of astrophysical models and related inference problems
- the analysis of heterogeneous data stemming from various sources or technical platforms