Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors

19 May 2024

Papers citing "Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors"

8 / 8 papers shown

Title
ICAFS: Inter-Client-Aware Feature Selection for Vertical Federated Learning Ruochen Jin Boning Tong Shu Yang Bojian Hou Li Shen 26 0 0 15 Apr 2025
FedSKD: Aggregation-free Model-heterogeneous Federated Learning using Multi-dimensional Similarity Knowledge Distillation Ziqiao Weng Weidong (Tom) Cai Bo Zhou 51 0 0 23 Mar 2025
Robust Dataset Distillation by Matching Adversarial Trajectories Wei Lai Tianyu Ding ren dongdong Lei Wang Jing Huo Yang Gao Wenbin Li AAML DD 57 0 0 15 Mar 2025
No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy" Nicholas Carlini Vitaly Feldman Milad Nasr DD 45 17 0 29 Sep 2022
FedMe: Federated Learning via Model Exchange Koji Matsuda Yuya Sasaki Chuan Xiao Makoto Onizuka FedML 45 19 0 15 Oct 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 153 459 0 01 May 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 196 288 0 16 Feb 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 279 10,354 0 12 Dec 2018