DEDALE: Data Learning on Manifolds and Future Challenges
Dates: 10/2015 – 09/2018
Funded by: : European Commission, H2020-FET-OPEN-2014
Project Coordinator: Jean Luc Starck (CEA/Saclay, France)
PI: P. Tsakalides
Funding: total cost/funding: € 2,702,398, FORTH-ICS cost/funding: € 560,000
Summary: The DEDALE interdisciplinary project intends to develop the
next generation of data analysis methods for such data set in order to probe the fine structureand extract information in high dimensional data sets, in astrophysics and remote sensing.
The project have three main scientific directions:
i) Introduce new models and methods to analyze and restore complex, multivariate, manifold-based signals,
ii) Exploit the current knowledge in optimization and operations research to build efficient numerical data processing algorithms in the large-scale settings,
iii) Show the reliability of the proposed methods in two different applications: one in cosmology and one in remote sensing.
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