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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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(morphological patterns), based on the experts’ knowledge. Then, tools like Procrustes analysis, linear dimensionality reduction (PCA) and standard clustering algorithms are employed. A first objective of our
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, situated within the Institut Pasteur, is a collaborative unit involving Pasteur, INRIA, CNRS, and UPC. Led by a Principal Investigator (PI), Jean-Baptiste Masson, who is a theoretical physicist, the lab is