SyDAG-FL

联邦学习模块化框架，支持各类FL。A universal federated learning framework, free to switch thread and process modes

SecMML (Queqiao): Secure MPC (multi-party computation) Machine Learning Framework.

P2PFL is a decentralized federated learning library that enables federated learning on peer-to-peer networks using gossip protocols, making collaborative AI model training possible without reliance on central servers.

HEFT, randomHEFT and IPEFT algorithms for static list DAG Scheduling

Unleash the true power of scheduling

[ICLR 2024] FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler

[ICLR 2025 Spotlight] LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs

Implementation of asynchronous federated learning in flower.

Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees

This is the code of paper entitled "AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection".