6 papers
FairGU: Fairness-aware Graph Unlearning in Social Networks
Renqiang Luo, Yongshuai Yang, Huafei Huang +6
Graph unlearning has emerged as a critical mechanism for supporting sustainable and privacy-preserving social networks, enabling models to remove the influence of deleted nodes and…
Optimal Cox regression under federated differential privacy: coefficients and cumulative hazards
Elly K. H. Hung, Yi Yu
We study two canonical problems in distributed survival analysis under federated differential privacy (FDP): estimation of cumulative hazard functions and Cox regression coefficien…
A hierarchy tree data structure for behavior-based user segment representation
Yang Liu, Xuejiao Kang, Sathya Iyer +10
User attributes are essential in multiple stages of modern recommendation systems and are particularly important for mitigating the cold-start problem and improving the experience…
Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models
Qianshan Wei, Jiaqi Li, Zihan You +9
Differential Privacy (DP) is a widely adopted technique, valued for its effectiveness in protecting the privacy of task-specific datasets, making it a critical tool for large langu…
Locally Differentially Private Two-Sample Testing
Alexander Kent, Thomas B. Berrett, Yi Yu
We consider the problem of two-sample testing under a local differential privacy constraint where a permutation procedure is used to calibrate the tests. We develop testing procedu…
Rate Optimality and Phase Transition for User-Level Local Differential Privacy
Alexander Kent, Thomas B. Berrett, Yi Yu
Most of the literature on differential privacy considers the item-level case where each user has a single observation, but a growing field of interest is that of user-level privacy…