Machine Learning

We work on the mathematical foundations of modern learning techniques and algorithms. More precisely, we currently develop tools for dimensionality reduction and clustering, neural networks, and reinforcement learning.

Our research is inter-disciplinary, as we leverage methods from statistics, optimization, and computer science, towards a better understanding of the design principles behind learning algorithms. Our projects in machine learning are often motivated by applications in communication systems and networks, online services, and social networks.  

Involved faculty

Belongs to: Decision and Control Systems
Last changed: Feb 09, 2018