Federated learning for generalization, robustness, fairness: A survey and benchmark
Federated learning has emerged as a promising paradigm for privacy-preserving
collaboration among different parties. Recently, with the popularity of federated learning, an …
collaboration among different parties. Recently, with the popularity of federated learning, an …
[PDF][PDF] Fisher calibration for backdoor-robust heterogeneous federated learning
Federated learning presents massive potential for privacyfriendly vision task collaboration.
However, the federated visual performance is deeply affected by backdoor attacks, where …
However, the federated visual performance is deeply affected by backdoor attacks, where …
Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning
Backdoor attacks pose a serious threat to federated systems, where malicious clients
optimize on the triggered distribution to mislead the global model towards a predefined …
optimize on the triggered distribution to mislead the global model towards a predefined …
Efficient Cloud-Sourced Transport Mode Detection Using Trajectory Data: A Semi-Supervised Asynchronous Federated Learning Approach
The Internet of Things enables collaborative efforts in pattern recognition tasks within
intelligent transportation systems, such as transport mode detection (TMD). However …
intelligent transportation systems, such as transport mode detection (TMD). However …
Fisher Calibration for Backdoor-Robust Heterogeneous Federated Learning
D Tao - Springer
Federated learning presents massive potential for privacyfriendly vision task collaboration.
However, the federated visual performance is deeply affected by backdoor attacks, where …
However, the federated visual performance is deeply affected by backdoor attacks, where …