Lecture series on algorithms and probability

Gábor Lugosi

We present some basic probabilistic tools that have applications in diverse areas of discrete mathematics, including the first and second moment methods, Chernoff bounds, concentration inequalities, and basics of branching processes. These techniques are put to work in the analysis of random graphs but some other applications are also shown.

Gábor has made his notes available.

About the speaker

Gábor Lugosi holds a degree in Electronic Engineering from the Budapest University of Technology and a PhD in Electronic Engineering (1991) from the Hungarian Academy of Sciences. He is currently an ICREA Research Professor at the Pompeu Fabra University Department of Economics. Formerly, he had been a lecturer at the Department of Mathematics and Computational Science of the Budapest University of Technology.

He is the coauthor of four books on pattern recognition; density estimation; prediction, learning, and games; and concentration inequalities. He has acted as editor or guest editor for many journals, including the Butlletí de la Societat Catalana de Matemàtiques, the Machine Learning Journal, Foundations and Trends in Machine Learning, the International Journal of Statistics and Management Systems, Constructive Approximation, ESAIM: Probability and Statistics, Statistics and Decisions, Test, and IEEE Transactions on Information Theory.