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The LEMUR Project

Learning with Multiple Representations

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Aim of the Project

LeMuR is an MSCA (Marie Skłodowska-Curie Actions) Doctoral Network (DN) 2021 on Learning with Multiple Representations. The goal of LeMuR is to develop the theoretical foundations and a first set of algorithms for the new “Learning with Multiple Representations” (LMR) paradigm. Moreover, corresponding applications will be developed to demonstrate the usefulness of the new family of approaches.
Specifically, LMR algorithms will allow flexible representations (e.g., suitable for explainability, fairness, …) with diverse target functions (e.g., incorporating environmental or even social impact) so as to make the induced models abide by the Green Charter and trustworthy AI criteria by design. The project will focus on learning with weak supervision because it addresses one of the major flaws of modern ML approaches, i.e., their data hunger, by means of weaker sources of labeling for training data. The outcome of the DN will be a set of 10 experts trained to implement the third and subsequent waves of AI in Europe. The highly interdisciplinary and intersectoral context in which they will be trained will provide them with research-related and transferable competencies relevant to successful careers in central AI areas.
Lemur objectives
Lemur objectives

List of Beneficiaries

  • Universitaet Paderborn, Germany
  • Universitaet Bielefeld, Germany
  • Ludwig-Maximilians-Universitaet Muenchen, Germany
  • Politechnika Poznanska, Poland
  • Katholieke Universiteit Leuven, Belgium
  • Università degli Studi di Milano-Bicocca, Italy
  • University of Cyprus, Cyprus
  • Università degli Studi di Siena, Italy
  • Stichting Vu, The Netherlands
  • Umea Universitet, Sweden
Lemur objectives

HORIZON Unit Grant