CORDIS Project
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ScReeningData develops a scalable learning framework to enhance data analysis in high-dimensional settings, particularly in genomics. By employing randomized controlled experiments with computer-generated controls, it aims to reduce computational complexity and improve the reliability of discoveries in various scientif…
Data science has quickly expanded the boundaries of signal processing and statistical learning beyond their accustomed domains.
Powerful and complex machine learning architectures have evolved to distinguish relevant information from randomness, artifacts and irrelevant data.
However, existing learning frameworks lack computationally scalable, tractable, and robust methods for high-dimensional data.
Consequently, discoveries, for example, in genomic data can be the result of coincidental finding…
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