Spectral and Optimization Techniques for Robust Recovery, Combinatorial Constructions, and Distributed Algorithms

Project description

Making sense of complex data and relationships

Models are integral to advancing our understanding of the world around us. Once we have developed them, we can change parameters to test hypotheses and evaluate potential outcomes. Model construction, though, is partially based on observations from which we extract certain 'rules' or behaviours, mathematical descriptions of relationships that form the algorithms of the models themselves. Recovering the 'structure' of data can be a very complicated task. The EU-funded SO-ReCoDi project will develop robust recovery algorithms applicable to several challenging problems through a unification of multiple advanced techniques.

Fields of science

• engineering and technology › electrical engineering, electronic engineering, information engineering › electronic engineering › sensors › smart sensors
• natural sciences › computer and information sciences › computational science
• natural sciences › computer and information sciences › artificial intelligence › machine learning

Programme(s)

• H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme

Topic(s)

• ERC-2018-ADG - ERC Advanced Grant

Call for proposal

ERC-2018-ADG

See other projects for this call

Funding Scheme

ERC-ADG - Advanced Grant

Host institution

UNIVERSITA COMMERCIALE LUIGI BOCCONI

Net EU contribution

€ 1 971 805,00

Address

Via Sarfatti 25
20136 Milano
Italy

Region

Nord-Ovest › Lombardia › Milano

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 0,00

Beneficiaries (1)

UNIVERSITA COMMERCIALE LUIGI BOCCONI

Italy

Net EU contribution

€ 1 971 805,00

Address

Via Sarfatti 25
20136 Milano

Region

Nord-Ovest › Lombardia › Milano

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 0,00