Gábor Lugosi received his PhD from the Hungarian Academy of Sciences in 1991 in electrical engineering. Since September 1996, he has been at the Department of Economics, Pompeu Fabra University. He became ICREA Research Professor in 2006.
Gábor Lugosi
Universitat Pompeu Fabra
Social & Behavioural Sciences
Research interests
Gábor Lugosi has mostly worked on the mathematics of machine learning, probability, mathematical statistics, information theory, and game theory. His research has been motivated by applications in telecommunications and computer science and also by game-theoretic learning. Recently he has mostly worked on high-dimensional problems in statistics, random graphs, "on-line" learning and sequential optimization, and inequalities in probability theory.
Selected publications
- Arias-Castro E, Bubeck S, Lugosi G & Verzelen N 2018, 'Detecting Markov random fields hidden in white noise', Bernoulli' 24, 4B, 3628 - 3656.
- Devroye L, Györfi L, Lugosi G & Walk H. 2018, 'A nearest neighbor estimate of the residual variance.' Electronic Journal of Statistics, Vol. 12, No. 1, 1752-1778,
- Barigozzi M, Brownlees C & Lugosi G 2018, 'On the consequence, of power-law behavior in partial correlation network models'. Electronic Journal of Statistics, Vol. 12, No. 2, 2905-2929, 2018.
Selected research activities
- Co-organizer of a month-long thematic activity on Mathematics of Machine Learning at the Centre de Recherches Mathématiques in Montréal, Canada.
- Invited participant of the Foundations of Data Science Fall program at the Simons Institute, Berkeley, CA.
- TRIAD Distinguished Lecturer at Georgia Tech.