ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.01264
  4. Cited By
HeteroFL: Computation and Communication Efficient Federated Learning for
  Heterogeneous Clients

HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

3 October 2020
Enmao Diao
Jie Ding
Vahid Tarokh
    FedML
ArXivPDFHTML

Papers citing "HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients"

27 / 77 papers shown
Title
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning
Daoyuan Chen
Dawei Gao
Weirui Kuang
Yaliang Li
Bolin Ding
FedML
30
64
0
08 Jun 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated
  Ensemble Learning
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning
Meisam Hejazinia
Dzmitry Huba
Ilias Leontiadis
Kiwan Maeng
Mani Malek
Luca Melis
Ilya Mironov
Milad Nasr
Kaikai Wang
Carole-Jean Wu
FedML
9
5
0
07 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the
  Inter-Dependence of System and Data Heterogeneity
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity
Kiwan Maeng
Haiyu Lu
Luca Melis
John Nguyen
Michael G. Rabbat
Carole-Jean Wu
FedML
39
31
0
30 May 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning
DELTA: Diverse Client Sampling for Fasting Federated Learning
Lung-Chuang Wang
Yongxin Guo
Tao R. Lin
Xiaoying Tang
FedML
23
22
0
27 May 2022
Decentralized Event-Triggered Federated Learning with Heterogeneous
  Communication Thresholds
Decentralized Event-Triggered Federated Learning with Heterogeneous Communication Thresholds
Shahryar Zehtabi
Seyyedali Hosseinalipour
Christopher G. Brinton
FedML
34
15
0
07 Apr 2022
FedCos: A Scene-adaptive Federated Optimization Enhancement for
  Performance Improvement
FedCos: A Scene-adaptive Federated Optimization Enhancement for Performance Improvement
Hao Zhang
Tingting Wu
Siyao Cheng
Jie Liu
FedML
35
11
0
07 Apr 2022
Bitwidth Heterogeneous Federated Learning with Progressive Weight
  Dequantization
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
Jaehong Yoon
Geondo Park
Wonyong Jeong
Sung Ju Hwang
FedML
24
19
0
23 Feb 2022
Federated Learning Challenges and Opportunities: An Outlook
Federated Learning Challenges and Opportunities: An Outlook
Jie Ding
Eric W. Tramel
Anit Kumar Sahu
Shuang Wu
Salman Avestimehr
Tao Zhang
FedML
33
55
0
01 Feb 2022
On the Convergence of Heterogeneous Federated Learning with Arbitrary
  Adaptive Online Model Pruning
On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning
Hanhan Zhou
Tian-Shing Lan
Guru Venkataramani
Wenbo Ding
FedML
32
6
0
27 Jan 2022
Federated Learning with Heterogeneous Architectures using Graph
  HyperNetworks
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
Or Litany
Haggai Maron
David Acuna
Jan Kautz
Gal Chechik
Sanja Fidler
FedML
38
24
0
20 Jan 2022
A Multi-agent Reinforcement Learning Approach for Efficient Client
  Selection in Federated Learning
A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning
S. Zhang
Jieyu Lin
Qi Zhang
35
63
0
09 Jan 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on
  Heterogeneous Clients
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients
Jaemin Shin
Yuanchun Li
Yunxin Liu
Sung-Ju Lee
FedML
17
73
0
05 Jan 2022
SPIDER: Searching Personalized Neural Architecture for Federated
  Learning
SPIDER: Searching Personalized Neural Architecture for Federated Learning
Erum Mushtaq
Chaoyang He
Jie Ding
A. Avestimehr
FedML
24
20
0
27 Dec 2021
Towards Federated Learning on Time-Evolving Heterogeneous Data
Towards Federated Learning on Time-Evolving Heterogeneous Data
Yongxin Guo
Tao R. Lin
Xiaoying Tang
FedML
22
30
0
25 Dec 2021
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems
Martin Rapp
R. Khalili
Kilian Pfeiffer
J. Henkel
19
18
0
16 Dec 2021
Semantic-Aware Collaborative Deep Reinforcement Learning Over Wireless
  Cellular Networks
Semantic-Aware Collaborative Deep Reinforcement Learning Over Wireless Cellular Networks
Fatemeh Lotfi
Omid Semiari
Walid Saad
27
27
0
23 Nov 2021
Personalized Federated Learning through Local Memorization
Personalized Federated Learning through Local Memorization
Othmane Marfoq
Giovanni Neglia
Laetitia Kameni
Richard Vidal
FedML
27
87
0
17 Nov 2021
Federated Learning for Internet of Things: Applications, Challenges, and
  Opportunities
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
Tuo Zhang
Lei Gao
Chaoyang He
Mi Zhang
Bhaskar Krishnamachari
Salman Avestimehr
FedML
19
168
0
15 Nov 2021
Practical and Light-weight Secure Aggregation for Federated Submodel
  Learning
Practical and Light-weight Secure Aggregation for Federated Submodel Learning
Jamie Cui
Cen Chen
Tiandi Ye
Li Wang
FedML
31
2
0
02 Nov 2021
What Do We Mean by Generalization in Federated Learning?
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan
Warren Morningstar
Lin Ning
K. Singhal
OOD
FedML
41
71
0
27 Oct 2021
Federated Learning via Plurality Vote
Federated Learning via Plurality Vote
Kai Yue
Richeng Jin
Chau-Wai Wong
H. Dai
FedML
24
8
0
06 Oct 2021
Comfetch: Federated Learning of Large Networks on Constrained Clients
  via Sketching
Comfetch: Federated Learning of Large Networks on Constrained Clients via Sketching
Tahseen Rabbani
Brandon Yushan Feng
Marco Bornstein
Kyle Rui Sang
Yifan Yang
Arjun Rajkumar
A. Varshney
Furong Huang
FedML
59
2
0
17 Sep 2021
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained
  Federated Learning with Heterogeneous On-Device Models
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models
Lan Zhang
Dapeng Wu
Xiaoyong Yuan
FedML
38
47
0
08 Sep 2021
An Operator Splitting View of Federated Learning
An Operator Splitting View of Federated Learning
Saber Malekmohammadi
K. Shaloudegi
Zeou Hu
Yaoliang Yu
FedML
26
2
0
12 Aug 2021
Membership Inference Attacks on Machine Learning: A Survey
Membership Inference Attacks on Machine Learning: A Survey
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Philip S. Yu
Xuyun Zhang
MIACV
35
412
0
14 Mar 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
841
0
01 Mar 2021
Threats to Federated Learning: A Survey
Threats to Federated Learning: A Survey
Lingjuan Lyu
Han Yu
Qiang Yang
FedML
202
434
0
04 Mar 2020
Previous
12