Machine Learning

Research Area Coordinator
Laetitia Emilie Gauvin, André Panisson

The Machine Learning research area is designed to study a range of topics related to theoretical foundations and applications of machine learning in various contexts such as computer vision, natural language processing, finance, mobility, health care and bioinformatics. The work is interdisciplinary and deeply rooted in the research areas of complex networks, complex systems and computer science. The research focuses on modelling and simulation of systems that involve technological and social factors, using both supervised and unsupervised machine learning techniques to investigate the properties of such systems.

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Publications

Gender gaps in urban mobility

L. E. Gauvin, M. Tizzoni, S. Piaggesi, A. Young, N. Adler, S. G. Verhulst, L. Ferres, C. Cattuto

Humanities and Social Sciences Communications 7/11 (2020)

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Generating Realistic Interest-Driven Information Cascades

F. Cinus, F. Bonchi, C. Monti, A. Panisson

Proceedings of The 14th International AAAI Conference on Web and Social Media (ICWSM 2020) ©AAAI, June 8-11, 2020, Atlanta, Georgia, USA (2020)

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FaiRecSys: mitigating algorithmic bias in recommender systems

B. Edizel, F. Bonchi, S. Hajian, A. Panisson, T. Tassa

International Journal of Data Science and Analytics 9 (2020)

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