We can announce another hot topic speaker for the YSS19:
Marco Cuturi is working in machine learning and in particular its connections to optimal transport. In his research he aims to extend optimal transport using entropic regularization, which has increased interest in optimal transport and Wasserstein distances in the machine learning community. His recent work is focused in applying that loss function to problems involving general probability distributions.
We are keen to hear more about his research at inter alia the global player Google.
More information about all our speakers can be found here.