Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups

5 November 2021

Papers citing "Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups"

7 / 7 papers shown

Title
Technical Insights and Legal Considerations for Advancing Federated Learning in Bioinformatics Daniele Malpetti Marco Scutari Francesco Gualdi Jessica van Setten Sander van der Laan Saskia Haitjema Aaron Mark Lee Isabelle Hering Francesca Mangili FedML AI4CE 98 1 0 12 Mar 2025
A Survey on Gradient Inversion: Attacks, Defenses and Future Directions Rui Zhang Song Guo Junxiao Wang Xin Xie Dacheng Tao 27 36 0 15 Jun 2022
Pretrained Transformers for Text Ranking: BERT and Beyond Jimmy J. Lin Rodrigo Nogueira Andrew Yates VLM 219 608 0 13 Oct 2020
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 162 564 0 27 Jul 2020
GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition Y. Kim Wonpyo Park Myung-Cheol Roh Jongju Shin CVBM 44 88 0 21 May 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 186 433 0 04 Mar 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,031 0 29 Nov 2018