Gergely Neu

Post-doctoral Researcher, UPF

Gergely Neu

PhD, Budapest University of Technology and Economics

I am a machine learning researcher mainly interested in theoretical aspects of sequential decision making. I mainly work on online optimization, bandit problems, and reinforcement learning theory. My general research mission is to bring theory and practice closer together by proving theoretical performance guarantees of practical algorithms and making principled learning algorithms more accessible to practicioners.

Publications

Luc P Devroye, Gábor Lugosi and Gergely Neu

Random-Walk Perturbations for Online Combinatorial Optimization

IEEE Transactions on Information Theory, Vol.61, No 7, 4099--4106, January 2015, 10.1109/TIT.2015.2428253