Papers accepted at AISTATS 2021

We got two papers accepted at this year’s AISTATS conference: “False Discovery Rates in Biological Networks” with Lu Yu and Tobias Kaufmann and “Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery” with Mike Laszkiewicz and Asja Fischer. Congratulations especially to the PhD students Lu (Toronto) and Mike (Bochum)! 🥳

Inference in Labor Economics

We have now put our paper “A pipeline for variable selection and false discovery rate control with an application in labor economics” on arXiv. The paper will be part of the Annual Congress of the Swiss Society of Economics and Statistics in 2021. Congratulations Sophie-Charlotte!

FDR Control in Labor Economics

Our paper A Pipeline for Variable Selection and False Discovery Rate Control with an Application in Labor Economics has been accepted for presentation at the 2020 Annual Congress of the Swiss Society of Economics and Statistics. Congratulations to Sophie-Charlotte Klose! Very impressive!

High-dimensional Inference

Our paper Inference for high-dimensional instrumental variables regression has been accepted by the Journal of Econometrics. Wonderful work from my co-authors Jing (faculty at University of Washington) and David (former student at University of Washington)! ✈

Paper on Oracle Inequalities Accepted

Our paper “Oracle Inequalities for High-dimensional Prediction” has been accepted for publication in the Bernoulli journal. Find an updated version here. Congratulations to Lu Yu, then Master’s student at UW and now PhD student at University of Toronto, and Irina Gaynanova, Assistant Professor at Texas A&M.