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 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.
– Lugosi G & Mendelson S 2019, ‘Sub-Gaussian estimators of the mean of a random vector’, Annals of Statistics, Vol. 47, No. 2, 783-794.
– Lugosi G & Mendelson S 2019, ‘Near-optimal mean estimators with respect to general norms’, Probability Theory and Related Fields, 175, 3-4, 957 – 973.
– Addario-Berry L, Devroye L, Lugosi G & Imbuzeiro Oliveira R 2019, ‘Local optima of the Sherrington-Kirkpatrick Hamiltonian’, Journal of Mathematical Physics, 60, 4, 043301.
– Lugosi G & Mendelson S 2019, ‘Mean estimation and regression under heavy-tailed distributions—a survey’, Foundations of Computational Mathematics,19(5), 1145-1190.
– Lugosi G & Mendelson S 2019, ‘Regularization, sparse recovery, and median-of-means tournaments’, Bernoulli, Vol. 25, No. 3, 2075-2106.