Depeng got a paper accepted at KDD 2021!

The paper entitled “Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent” by Depeng Xu,  Wei Du, and Xintao Wu has been accepted as a regular paper at the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Aug 14-18, 2021. This year the selection process was very competitive, there were 1541 submissions and 238 of them were accepted (acceptance rate of 15.4%). Congratulations, Depeng and Wei!