CISE Seminar: October 4, 2019 – Lorenzo Rosasco, Massachusetts Institute of Technology (MIT)

8 St. Mary’s Street, PHO 203
3:00pm-4:00pm

Lorenzo Rosasco 

Visiting Professor
Massachusetts Institute of Technology (MIT)

Not So Fast: Learning With Accelerated Optimization 

The focus on optimization is a major trend in modern machine learning. In turn, a number of optimization solutions have been recently developed and motivated by machine learning applications. However, most optimization guarantees focus on the training error, ignoring the performance at test time, which is the real goal in machine learning. In this talk, take steps to fill this gap in the context of least squares learning. We analyze the learning (test) performance of accelerated and stochastic gradient methods. In particular, we discuss the influence of different learning assumptions.

Lorenzo Rosasco is a full-time professor at University of Genova. He is also a visiting professor at the Massachusetts Institute of Technology (MIT) and external collaborator at the Italian Technological Institute (IIT). He coordinates the Machine Learning Genova center (MaLGa) and leads the Laboratory for Computational and Statistical Learning, which is focused on theory, algorithms and application of machine learning.

Lorenzo received his PhD in 2006 from the University of Genova, after being a visiting student at the Center for Biological and Computational Learning at MIT, the Toyota Technological Institute at Chicago (TTI-Chicago) and the Johann Radon Institute for Computational and Applied Mathematics. Between 2006 and 2013, he has been a post-doctoral and research scientist at the Brain and Cognitive Sciences Department at MIT. He is a recipient of numerous grants, including a FIRB and an ERC consolidator.

Faculty Hosts: Venkatesh Saligrama & Francesco Orabona
Student Host: Arian Houshmand