Projects based on EasyFL

We have been doing research on federated learning for several years and published several papers in top-tier conferences and journals. EasyFL is developed based on deep insights from our research. It further facilitated us built other federated learning several projects.

Applications

We have released the following implementations of federated learning applications:

• Federated Multiple Task Learning: [code] for MAS: Towards Resource-Efficient Federated Multiple-Task Learning (ICCV’2023)

• FedReID: [code] for Performance Optimization for Federated Person Re-identification via Benchmark Analysis (ACMMM’2020).

• FedSSL: [code] for two papers: Divergence-aware Federated Self-Supervised Learning (ICLR’2022) and Collaborative Unsupervised Visual Representation Learning From Decentralized Data (ICCV’2021)

Papers

The following are the projects and papers built on EasyFL:

• EasyFL: A Low-code Federated Learning Platform For Dummies, IEEE Internet-of-Things Journal. [paper]

• Divergence-aware Federated Self-Supervised Learning, ICLR’2022. [paper]

• Collaborative Unsupervised Visual Representation Learning From Decentralized Data, ICCV’2021. [paper]

• Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification, ACMMM’2021. [paper]

If you have built new projects using EasyFL, please feel free to create PR to update this page.