Paper "differential privacy" Papers
11 papers found
Conference
A New Federated Learning Framework Against Gradient Inversion Attacks
Pengxin Guo, Shuang Zeng, Wenhao Chen et al.
AAAI 2025paperarXiv:2412.07187
8
citations
Differentially Private Prototypes for Imbalanced Transfer Learning
Dariush Wahdany, Matthew Jagielski, Adam Dziedzic et al.
AAAI 2025paperarXiv:2406.08039
2
citations
DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models
Yanming Liu, Xinyue Peng, Yuwei Zhang et al.
AAAI 2025paperarXiv:2406.11087
3
citations
Federated Binary Matrix Factorization Using Proximal Optimization
Sebastian Dalleiger, Jilles Vreeken, Michael Kamp
AAAI 2025paperarXiv:2407.01776
Federated t-SNE and UMAP for Distributed Data Visualization
Dong Qiao, Xinxian Ma, Jicong Fan
AAAI 2025paperarXiv:2412.13495
2
citations
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
Haoteng Yin, Rongzhe Wei, Eli Chien et al.
COLM 2025paperarXiv:2410.08299
1
citations
PrivateXR: Defending Privacy Attacks in Extended Reality Through Explainable AI-Guided Differential Privacy
Ripan Kumar Kundu, Istiak Ahmed, Khaza Anuarul Hoque
ISMAR 2025paperarXiv:2512.16851
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)
Qiaoyue Tang, Frederick Shpilevskiy, Mathias Lécuyer
AAAI 2024paperarXiv:2312.14334
30
citations
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation
Nimesh Agrawal, Anuj Sirohi, Sandeep Kumar et al.
AAAI 2024paperarXiv:2312.10080
39
citations
Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding
Yuecen Wei, Haonan Yuan, Xingcheng Fu et al.
AAAI 2024paperarXiv:2312.12183
11
citations
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions
T-H. Hubert Chan, Hao Xie, Mengshi ZHAO
AAAI 2024paperarXiv:2312.08685
1
citations