Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models
Authors: Yuanbin Cheng, Koji Yamashita, Jim Follum, Nanpeng Yu | Published: 2023-11-13
最適化問題
A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning
Authors: Spencer Giddens, Yiwang Zhou, Kevin R. Krull, Tara M. Brinkman, Peter X. K. Song, Fang Liu | Published: 2023-07-24 | Updated: 2024-09-27
The importance of feature preprocessing for differentially private linear optimization
Authors: Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon | Published: 2023-07-19 | Updated: 2024-02-19
Optimal Differentially Private Model Training with Public Data
Authors: Andrew Lowy, Zeman Li, Tianjian Huang, Meisam Razaviyayn | Published: 2023-06-26 | Updated: 2024-09-09
Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy
Authors: Kang Wei, Jun Li, Chuan Ma, Ming Ding, Feng Shu, Haitao Zhao, Wen Chen, Hongbo Zhu | Published: 2023-04-09 | Updated: 2023-12-21
Reliable learning in challenging environments
Authors: Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma | Published: 2023-04-06 | Updated: 2023-10-29
Practical Differentially Private Hyperparameter Tuning with Subsampling
Authors: Antti Koskela, Tejas Kulkarni | Published: 2023-01-27 | Updated: 2024-02-13
Pareto Regret Analyses in Multi-objective Multi-armed Bandit
Authors: Mengfan Xu, Diego Klabjan | Published: 2022-12-01 | Updated: 2023-05-30
Hijack Vertical Federated Learning Models As One Party
Authors: Pengyu Qiu, Xuhong Zhang, Shouling Ji, Changjiang Li, Yuwen Pu, Xing Yang, Ting Wang | Published: 2022-12-01 | Updated: 2024-02-16
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
Authors: Hong-Ming Chiu, Richard Y. Zhang | Published: 2022-11-30 | Updated: 2023-06-14