BiographyWouter M. Koolen works on topics in machine learning theory and related areas, including game theory, information theory, statistics and optimisation. My current interests include pure exploration in multi-armed bandit models, game tree search, and provably accelerated learning in statistical and individual-sequence settings, aka learning faster from easy data. Koolen is a member of the INRIA-CWI associate teams 6PAC with Inria Lille and 4TUNE with Inria Paris and Grenoble. He is an ELLIS Scholar.
I work on topics in machine learning and related areas, including game theory, information theory, statistics and optimisation.
My current projects are
- Game tree search
- Learning faster from easy data
- Online learning beyond experts
- Minimax square loss prediction
- Online Finance
- Switching Experts
- Non-uniform regret analysis
- Robust statistics
- Algorithmic information theory