| Robustness, Privacy, and Generalization of Adversarial Training | Dec 25, 2020 | Generalization BoundsPrivacy Preserving | CodeCode Available | 0 |
| Towards the efficacy of federated prediction for epidemics on networks | Dec 3, 2024 | Federated LearningGraph Attention | CodeCode Available | 0 |
| Differentially Private Distributed Inference | Feb 13, 2024 | Decision MakingPrivacy Preserving | CodeCode Available | 0 |
| Privacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific Features | Nov 11, 2019 | Privacy Preserving | CodeCode Available | 0 |
| Position: On-Premises LLM Deployment Demands a Middle Path: Preserving Privacy Without Sacrificing Model Confidentiality | Oct 15, 2024 | PositionPrivacy Preserving | CodeCode Available | 0 |
| GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption | Jan 26, 2024 | Privacy Preserving | CodeCode Available | 0 |
| Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations | Oct 26, 2021 | Multi-Domain Recommender SystemsPrivacy Preserving | CodeCode Available | 0 |
| Differentially Private Algorithms for Synthetic Power System Datasets | Mar 20, 2023 | Privacy Preserving | CodeCode Available | 0 |
| Handling Data Heterogeneity in Federated Learning via Knowledge Distillation and Fusion | Jul 23, 2022 | Data-free Knowledge DistillationFairness | CodeCode Available | 0 |
| Towards Fair and Privacy-Preserving Federated Deep Models | Jun 4, 2019 | BenchmarkingDeep Learning | CodeCode Available | 0 |
