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Statistical Physics, Information Theory, applied Probability and their application to machine learning, disordered materials and other compex systems.
Current projects include:
- Analysis of the generalization ability of neural nets and other learning machines using methods of Statistical Physics.
- General Bounds on entropic error measures in estimating probability distributions.
- Worst Case over sequence prediction.
- Mean Field methods in probabilistic modelling.
- Bayesian approaches to online learning.
- Nonequilibrium dynamics of disordered systems.
- Support Vector Machines
- Population dynamics.