| NO. | Beijing Time (UTC+8) | Type | Presentation Topic | Speaker | Affiliation / Organization |
|---|---|---|---|---|---|
| 1 | 13:30-13:55 | Invited Talk |
Learning Sparse Support under Differential Privacy: Minimax Rates and Adaptive Algorithms |
Jia Gu | Zhejiang University |
| 2 | 13:55-14:20 | Invited Talk |
Differentially Private Minimax and Adaptive Bandable Covariance Matrix Estimation |
Yicheng Li | East China Normal University |
| 3 | 14:20-14:45 | Invited Talk |
Private Decentralized Federated Learning with Random Walk |
Chendi Wang | Xiamen University |
| 4 | 14:45-15:10 | Invited Talk |
Statistical Inference for Differentially Private Stochastic Gradient Descent |
Xintao Xia | Zhejiang University |
| NO. | Beijing Time (UTC+8) | Type | Presentation Topic | Speaker | Affiliation / Organization |
|---|---|---|---|---|---|
| 1 | 15:30-15:55 | Invited Talk |
Knockoffs Inference under Privacy Constraints |
Lan Gao | University of Tennessee,Knoxville |
| 2 | 15:55-16:20 | Invited Talk |
Training-Free Multi-Agent Language Models |
Xiaowu Dai | University of California, Los Angeles |
| 3 | 16:20-16:45 | Invited Talk |
A Sparse Learning Framework for High-Dimensional Newsvendor under Privacy Constraints |
Yichen Zhang | Purdue University |
| 4 | 16:45-17:10 | Invited Talk |
Adapting to Noise Tails in Private Linear Regression |
Wenxin Zhou | University of Illinois Chicago |