Federated Learning with Privacy-Preserving Ensemble Attention Distillation

no code implementations • 16 Oct 2022 • Xuan Gong, Liangchen Song, Rishi Vedula, Abhishek Sharma, Meng Zheng, Benjamin Planche, Arun Innanje, Terrence Chen, Junsong Yuan, David Doermann, Ziyan Wu

We propose a privacy-preserving FL framework leveraging unlabeled public data for one-way offline knowledge distillation in this work.

Federated Learning Image Classification +2

Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation

no code implementations • 10 Sep 2022 • Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje

Federated Learning (FL) is a machine learning paradigm where local nodes collaboratively train a central model while the training data remains decentralized.

Federated Learning Image Classification +4

Ensemble Attention Distillation for Privacy-Preserving Federated Learning

no code implementations • ICCV 2021 • Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje

Such decentralized training naturally leads to issues of imbalanced or differing data distributions among the local models and challenges in fusing them into a central model.

Federated Learning Privacy Preserving