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)! 🥳

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!

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)! ✈

Our paper “Tuning parameter calibration for l1-regularized logistic regression” has been accepted at JSPI. Congratulations Wei! 🤠

Our paper “Maximum Regularized Likelihood Estimators: A General Prediction Theory and Applications” has been accepted in STAT. Congratulations, Rui! 😎

Our paper “Prediction Error Bounds for Linear Regression With the TREX” has been accepted in TEST. Thanks to Jacob, Irina, and Christian!

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.

Our paper on tuning parameter calibration for the Lasso has been accepted at JMLR. You can find an updated version here.