5 papers
Differentially Private Non-convex Distributionally Robust Optimization
Difei Xu, Meng Ding, Zebin Ma +4
Real-world deployments routinely face distribution shifts, group imbalances, and adversarial perturbations, under which the traditional Empirical Risk Minimization (ERM) framework…
Finding Differentially Private Second Order Stationary Points in Stochastic Minimax Optimization
Difei Xu, Youming Tao, Meng Ding +2
We provide the first study of the problem of finding differentially private (DP) second-order stationary points (SOSP) in stochastic (non-convex) minimax optimization. Existing lit…
Second-Order Convergence in Private Stochastic Non-Convex Optimization
Youming Tao, Zuyuan Zhang, Dongxiao Yu +3
We investigate the problem of finding second-order stationary points (SOSP) in differentially private (DP) stochastic non-convex optimization. Existing methods suffer from two key…
Certified Unlearning in Decentralized Federated Learning
Hengliang Wu, Youming Tao, Anhao Zhou +3
Driven by the right to be forgotten (RTBF), machine unlearning has become an essential requirement for privacy-preserving machine learning. However, its realization in decentralize…
Adaptive pruning-based Newton's method for distributed learning
Shuzhen Chen, Yuan Yuan, Youming Tao +3
Newton's method leverages curvature information to boost performance, and thus outperforms first-order methods for distributed learning problems. However, Newton's method is not pr…