Here are the main topics on which our group works.
Adversarial learning corresponds to trying to build models which are robust to malicious adversaries.
Understanding the performance of neural networks is certainly one of the most thrilling challenges for the current machine learning community.
The tremendous success of machine learning in recent years is largely due to the impressive performances of stochastic optimisation algorithms such as SGD.
Markov chain Monte Carlo (MCMC) algorithms are a powerful, computational tool for Bayesian inference.