arXiv:2402.10464
공식 코드 · Papers with Code
FedKit: Enabling Cross-Platform Federated Learning for Android and iOS
원문 초록
We present FedKit, a federated learning (FL) system tailored for cross-platform FL research on Android and iOS devices. FedKit pipelines cross-platform FL development by enabling model conversion, hardware-accelerated training, and cross-platform model aggregation. Our FL workflow supports flexible machine learning operations (MLOps) in production, facilitating continuous model delivery and training. We have deployed FedKit in a real-world use case for health data analysis on university campuses, demonstrating its effectiveness. FedKit is open-source at https://github.com/FedCampus/FedKit.
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FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning
Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection
Prototype-Guided and Lightweight Adapters for Inherent Interpretation and Generalisation in Federated Learning
FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift
BackFed: An Efficient & Standardized Benchmark Suite for Backdoor Attacks in Federated Learning
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