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VFedMH: Vertical Federated Learning for Training Multiple Heterogeneous
  Models

VFedMH: Vertical Federated Learning for Training Multiple Heterogeneous Models

20 October 2023
Shuo Wang
Keke Gai
Jing Yu
Liehuang Zhu
Kim-Kwang Raymond Choo
Bin Xiao
    FedML
ArXivPDFHTML

Papers citing "VFedMH: Vertical Federated Learning for Training Multiple Heterogeneous Models"

3 / 3 papers shown
Title
AsySQN: Faster Vertical Federated Learning Algorithms with Better
  Computation Resource Utilization
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
Qingsong Zhang
Bin Gu
Cheng Deng
Songxiang Gu
Liefeng Bo
J. Pei
Heng-Chiao Huang
FedML
95
30
0
26 Sep 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients
FedProto: Federated Prototype Learning across Heterogeneous Clients
Yue Tan
Guodong Long
Lu Liu
Tianyi Zhou
Qinghua Lu
Jing Jiang
Chengqi Zhang
FedML
151
455
0
01 May 2021
A Simple Convergence Proof of Adam and Adagrad
A Simple Convergence Proof of Adam and Adagrad
Alexandre Défossez
Léon Bottou
Francis R. Bach
Nicolas Usunier
56
143
0
05 Mar 2020
1