research
∙
09/10/2023
Outlier Robust Adversarial Training
Supervised learning models are challenged by the intrinsic complexities ...
share
research
∙
03/16/2023
Fairness-aware Differentially Private Collaborative Filtering
Recently, there has been an increasing adoption of differential privacy ...
research
∙
08/22/2022
Minimax AUC Fairness: Efficient Algorithm with Provable Convergence
The use of machine learning models in consequential decision making ofte...
research
∙
01/22/2022
Differentially Private SGDA for Minimax Problems
Stochastic gradient descent ascent (SGDA) and its variants have been the...
research
∙
11/23/2021
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning
Pairwise learning refers to learning tasks where the loss function depen...
research
∙
05/08/2021
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Many machine learning problems can be formulated as minimax problems suc...
research
∙
11/04/2020
Stochastic Hard Thresholding Algorithms for AUC Maximization
In this paper, we aim to develop stochastic hard thresholding algorithms...
research
∙
04/25/2019
