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
Richards, D. and Rebeschini, P. (2019) “Optimal statistical rates for decentralised non-parametric regression with linear speed-up”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Neural Information Processing Systems Foundation.
.
Tatikonda, S. and Rebeschini, P. (2018) “Accelerated consensus via Min-Sum Splitting”, in Advances in Neural Information Processing Systems 30: 31st Annual Conference on Neural Information Processing Systems (NIPS 2017). Curran Associates, pp. 1375–1385.