Adaptive Federated Pruning in Hierarchical Wireless Networks

Adaptive Federated Pruning in Hierarchical Wireless Networks

15 May 2023

Papers citing "Adaptive Federated Pruning in Hierarchical Wireless Networks"

10 / 10 papers shown

Title
Federated Dropout -- A Simple Approach for Enabling Federated Learning on Resource Constrained Devices Dingzhu Wen Ki-Jun Jeon Kaibin Huang FedML 95 91 0 30 Sep 2021
A Survey and Comparative Study on Multi-Cloud Architectures: Emerging Issues And Challenges For Cloud Federation D. Saxena Rishabh Gupta Ashutosh Kumar Singh 38 9 0 29 Aug 2021
Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks Chenyuan Feng Heng Yang Deshun Hu Zhiwei Zhao Tony Q.S. Quek Geyong Min 74 78 0 20 Aug 2021
Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning Dingzhu Wen M. Bennis Kaibin Huang 52 48 0 10 Mar 2020
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 59 461 0 26 Sep 2019
Importance Estimation for Neural Network Pruning Pavlo Molchanov Arun Mallya Stephen Tyree I. Frosio Jan Kautz 3DPC 76 879 0 25 Jun 2019
Client-Edge-Cloud Hierarchical Federated Learning Lumin Liu Jun Zhang S. H. Song Khaled B. Letaief FedML 67 741 0 16 May 2019
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 231 1,196 0 04 Oct 2018
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 285 6,660 0 08 Jun 2015
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 120 1,547 0 22 Sep 2013