Our paper “Statistical guarantees for regularized neural networks” has been accepted at Neural Networks. Congrats, Mahsa and Fang! 🧉
Our paper “Aggregated false discovery rate control” has been accepted at Entropy. Great job, Fang! 🎬
Our paper “Integrating additional knowledge into the estimation of graphical models” is now accepted at the International Journal of Biostatistics. Congratulations, Yunqi! ⛄
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)! 🥳
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!
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!