Spring 2022

Spring 2022

Feb 4th – Dan Mikulincer, (MIT)
The Brownian transport map

Feb 18th – Ilias Zadik, (MIT)
On the power of Lenstra-Lenstra-Lovasz in noiseless inference

Feb 25th – *POSTPONED* Yue Lu, (Harvard University)

Mar 4th – Edgar Dobriban, (University of Pennsylvania)
Optimal Testing for Calibration of Predictive Models

Mar 11th – Isaiah Andrews, (Harvard University)
Inference on Winners

Mar 18th – Subhabrata Sen (Harvard University)
Mean-field approximations for high-dimensional Bayesian Regression

Apr 8th – Li-Yang Tan, (Stanford University)
The query complexity of certification

April 15th – Caroline Uhler, (MIT)
Causal Representation Learning – A Proposal

Apr 22nd – Yue M. Lu, (Harvard University)
Learning with Random Features and Kernels: Sharp Asymptotics and Universality Laws

Apr 29th – Giedre Lideikyte-Huber and Marta Pittavino (University of Geneva)
Is quantile regression a suitable method to understand tax incentives for charitable giving? Case study from the Canton of Geneva, Switzerland

May 6th – Jonathan Weare (New York University)
Sampling rare events in Earth and planetary science

MIT Statistics + Data Science Center
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307