Privacy-preserving Federated Adversarial Domain Adaption over Feature
Groups for Interpretability

Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability

22 November 2021

Yang Liu

Papers citing "Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability"

12 / 12 papers shown

Title
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning Chengui Xiao Songbai Liu FedML 72 0 0 29 Apr 2025
UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration Chung-ju Huang Yuanpeng He Xiao Han Wenpin Jiao Zhi Jin Leye Wang FedML 41 2 0 20 Jan 2025
Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review Luis M. Lopez-Ramos Florian Leiser Aditya Rastogi Steven Hicks Inga Strümke V. Madai Tobias Budig Ali Sunyaev A. Hilbert 30 1 0 07 Nov 2024
Vertical Federated Learning with Missing Features During Training and Inference Pedro Valdeira Shiqiang Wang Yuejie Chi FedML 39 2 0 29 Oct 2024
Improving Source-Free Target Adaptation with Vision Transformers Leveraging Domain Representation Images Gauransh Sawhney Daksh Dave Adeel Ahmed Jiechao Gao Khalid Saleem 28 0 0 21 Nov 2023
Federated Learning without Full Labels: A Survey Yilun Jin Yang Liu Kai Chen Qian Yang FedML 12 26 0 25 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation Hanlin Gu Jiahuan Luo Yan Kang Lixin Fan Qiang Yang FedML 36 13 0 30 Jan 2023
Vertical Federated Learning: Concepts, Advances and Challenges Yang Liu Yan Kang Tianyuan Zou Yanhong Pu Yuanqin He Xiaozhou Ye Ye Ouyang Yaqin Zhang Qian Yang FedML 57 161 0 23 Nov 2022
Federated Deep Learning with Bayesian Privacy Hanlin Gu Lixin Fan Bowen Li Jie Li Yan Kang Yuan Yao Qiang Yang FedML 88 24 0 27 Sep 2021
Label Leakage and Protection in Two-party Split Learning Oscar Li Jiankai Sun Xin Yang Weihao Gao Hongyi Zhang Junyuan Xie Virginia Smith Chong-Jun Wang FedML 134 139 0 17 Feb 2021
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017