Recent & Upcoming Talks

In order to leave the factory floors and research labs, future robots must abandon their stiff and pre-programmed movements and be …

The use of Gaussian process models is typically limited to datasets with a few tens of thousands of observations due to their …

I will discuss multiple-data-source prediction and modelling problems arising in a number of fields, for instance in omics-based …

We derive a family of Monte Carlo estimators for gradients of expectations, which is related to the log-derivative trick, but involves …

In machine learning, new learning algorithms are designed by borrowing ideas from optimization and statistics followed by an extensive …