Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling

23 October 2022

Papers citing "Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling"

5 / 5 papers shown

Title
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions Weiming Zhuang Chen Chen Lingjuan Lyu C. L. P. Chen Yaochu Jin Lingjuan Lyu AIFin AI4CE 44 83 0 27 Jun 2023
CalFAT: Calibrated Federated Adversarial Training with Label Skewness Chen Chen Yuchen Liu Xingjun Ma Lingjuan Lyu FedML 115 23 0 30 May 2022
Leveraging Public Data for Practical Private Query Release Terrance Liu G. Vietri Thomas Steinke Jonathan R. Ullman Zhiwei Steven Wu 119 56 0 17 Feb 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 135 631 0 15 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 130 244 0 07 Dec 2020