Professor Patrick Rebeschini

Professor of Statistics and Machine Learning

Biographical Sketch

I have a Ph.D. in Operations Research and Financial Engineering from Princeton University (2014). After that, I joined the Yale Institute for Network Science at Yale University. I worked two years as a Postdoctoral Associate in the Electrical Engineering Department, and one year as an Associate Research Scientist with a joint appointment as a Lecturer in the Computer Science Department at Yale.

Research Interests

My research interests lie at the intersection of probability, statistics, and computer science. I am interested in the investigation of fundamental principles  in high-dimensional probability, statistics and optimisation to design computationally efficient and statistically optimal algorithms for machine learning.

Publications

Rebeschini, P. and Tatikonda, S. (2016) “Decay of Correlation in Network Flow Problems”, in 2016 ANNUAL CONFERENCE ON INFORMATION SCIENCE AND SYSTEMS (CISS).
Rebeschini, P. and Karbasi, A. (2015) “Fast mixing for discrete point processes”, in Journal of Machine Learning Research.
Alfano, C., Yuan, R. and Rebeschini, P. (no date) “A novel framework for policy mirror descent with general parameterization and linear convergence”, in. Curran Associates.

Contact Details

College affiliation: Tutorial Fellow at University College

Email: patrick.rebeschini@stats.ox.ac.uk