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. 1808.07576
  4. Cited By
Cooperative SGD: A unified Framework for the Design and Analysis of
  Communication-Efficient SGD Algorithms

Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms

22 August 2018
Jianyu Wang
Gauri Joshi
ArXivPDFHTML

Papers citing "Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms"

50 / 209 papers shown
Title
Review of Mathematical Optimization in Federated Learning
Review of Mathematical Optimization in Federated Learning
Shusen Yang
Fangyuan Zhao
Zihao Zhou
Liang Shi
Xuebin Ren
Zongben Xu
FedML
AI4CE
72
0
0
02 Dec 2024
Federated Learning with Integrated Sensing, Communication, and
  Computation: Frameworks and Performance Analysis
Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysis
Yipeng Liang
Qimei Chen
Hao Jiang
FedML
30
1
0
17 Sep 2024
A New Theoretical Perspective on Data Heterogeneity in Federated
  Optimization
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang
Shiqiang Wang
Rong-Rong Chen
Mingyue Ji
FedML
30
1
0
22 Jul 2024
DFedSat: Communication-Efficient and Robust Decentralized Federated
  Learning for LEO Satellite Constellations
DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations
Minghao Yang
Jingjing Zhang
Shengyun Liu
FedML
37
2
0
08 Jul 2024
Improved Generalization Bounds for Communication Efficient Federated
  Learning
Improved Generalization Bounds for Communication Efficient Federated Learning
Peyman Gholami
H. Seferoglu
FedML
AI4CE
23
6
0
17 Apr 2024
Dynamic Client Clustering, Bandwidth Allocation, and Workload
  Optimization for Semi-synchronous Federated Learning
Dynamic Client Clustering, Bandwidth Allocation, and Workload Optimization for Semi-synchronous Federated Learning
Liang Yu
Xiang Sun
Rana Albelaihi
Chaeeun Park
Sihua Shao
FedML
32
1
0
11 Mar 2024
Every Parameter Matters: Ensuring the Convergence of Federated Learning
  with Dynamic Heterogeneous Models Reduction
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
Hanhan Zhou
Tian-Shing Lan
Guru Venkataramani
Wenbo Ding
29
28
0
12 Oct 2023
DRAG: Divergence-based Adaptive Aggregation in Federated learning on
  Non-IID Data
DRAG: Divergence-based Adaptive Aggregation in Federated learning on Non-IID Data
Feng Zhu
Jingjing Zhang
Shengyun Liu
Xin Wang
FedML
19
1
0
04 Sep 2023
Guiding The Last Layer in Federated Learning with Pre-Trained Models
Guiding The Last Layer in Federated Learning with Pre-Trained Models
G. Legate
Nicolas Bernier
Lucas Caccia
Edouard Oyallon
Eugene Belilovsky
FedML
18
8
0
06 Jun 2023
Federated Multi-Sequence Stochastic Approximation with Local
  Hypergradient Estimation
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation
Davoud Ataee Tarzanagh
Mingchen Li
Pranay Sharma
Samet Oymak
24
0
0
02 Jun 2023
Theoretically Principled Federated Learning for Balancing Privacy and
  Utility
Theoretically Principled Federated Learning for Balancing Privacy and Utility
Xiaojin Zhang
Wenjie Li
Kai Chen
Shutao Xia
Qian Yang
FedML
22
9
0
24 May 2023
Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated
  Learning
Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning
G. Legate
Lucas Caccia
Eugene Belilovsky
FedML
34
10
0
11 Apr 2023
On the Local Cache Update Rules in Streaming Federated Learning
On the Local Cache Update Rules in Streaming Federated Learning
Heqiang Wang
Jieming Bian
Jie Xu
24
4
0
28 Mar 2023
Reducing Non-IID Effects in Federated Autonomous Driving with
  Contrastive Divergence Loss
Reducing Non-IID Effects in Federated Autonomous Driving with Contrastive Divergence Loss
Tuong Khanh Long Do
Binh X. Nguyen
Hien Nguyen
Erman Tjiputra
Quang-Dieu Tran
Te-Chuan Chiu
A. Nguyen
35
0
0
11 Mar 2023
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections
  for Federated Learning with Heterogeneous Data
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data
M. Crawshaw
Yajie Bao
Mingrui Liu
FedML
24
8
0
14 Feb 2023
Communication-Efficient Federated Hypergradient Computation via
  Aggregated Iterative Differentiation
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation
Peiyao Xiao
Kaiyi Ji
FedML
26
10
0
09 Feb 2023
Federated Temporal Difference Learning with Linear Function
  Approximation under Environmental Heterogeneity
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity
Han Wang
A. Mitra
Hamed Hassani
George J. Pappas
James Anderson
FedML
29
21
0
04 Feb 2023
Federated Learning for Appearance-based Gaze Estimation in the Wild
Federated Learning for Appearance-based Gaze Estimation in the Wild
Mayar Elfares
Zhiming Hu
Pascal Reisert
Andreas Bulling
Ralf Küsters
FedML
21
11
0
14 Nov 2022
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model
  Communication
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication
Marco Bornstein
Tahseen Rabbani
Evana Wang
Amrit Singh Bedi
Furong Huang
FedML
49
18
0
25 Oct 2022
Latency Aware Semi-synchronous Client Selection and Model Aggregation
  for Wireless Federated Learning
Latency Aware Semi-synchronous Client Selection and Model Aggregation for Wireless Federated Learning
Liang Yu
Xiang Sun
Rana Albelaihi
Chen Yi
FedML
32
13
0
19 Oct 2022
Random Orthogonalization for Federated Learning in Massive MIMO Systems
Random Orthogonalization for Federated Learning in Massive MIMO Systems
Xizixiang Wei
Cong Shen
Jing Yang
H. Vincent Poor
52
14
0
18 Oct 2022
STSyn: Speeding Up Local SGD with Straggler-Tolerant Synchronization
STSyn: Speeding Up Local SGD with Straggler-Tolerant Synchronization
Feng Zhu
Jingjing Zhang
Xin Wang
33
3
0
06 Oct 2022
SAGDA: Achieving $\mathcal{O}(ε^{-2})$ Communication Complexity
  in Federated Min-Max Learning
SAGDA: Achieving O(ε−2)\mathcal{O}(ε^{-2})O(ε−2) Communication Complexity in Federated Min-Max Learning
Haibo Yang
Zhuqing Liu
Xin Zhang
Jia-Wei Liu
FedML
30
0
0
02 Oct 2022
Flexible Vertical Federated Learning with Heterogeneous Parties
Flexible Vertical Federated Learning with Heterogeneous Parties
Timothy Castiglia
Shiqiang Wang
S. Patterson
FedML
31
34
0
26 Aug 2022
FedVARP: Tackling the Variance Due to Partial Client Participation in
  Federated Learning
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning
Divyansh Jhunjhunwala
Pranay Sharma
Aushim Nagarkatti
Gauri Joshi
FedML
44
42
0
28 Jul 2022
Reducing Training Time in Cross-Silo Federated Learning using Multigraph
  Topology
Reducing Training Time in Cross-Silo Federated Learning using Multigraph Topology
Tuong Khanh Long Do
Binh X. Nguyen
Vuong Pham
Toan V. Tran
Erman Tjiputra
Quang-Dieu Tran
A. Nguyen
FedML
AI4CE
33
3
0
20 Jul 2022
Multi-Model Federated Learning with Provable Guarantees
Multi-Model Federated Learning with Provable Guarantees
Neelkamal Bhuyan
Sharayu Moharir
Gauri Joshi
FedML
24
14
0
09 Jul 2022
Fundamental Limits of Communication Efficiency for Model Aggregation in
  Distributed Learning: A Rate-Distortion Approach
Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach
Naifu Zhang
M. Tao
Jia Wang
Fan Xu
11
13
0
28 Jun 2022
On the Unreasonable Effectiveness of Federated Averaging with
  Heterogeneous Data
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data
Jianyu Wang
Rudrajit Das
Gauri Joshi
Satyen Kale
Zheng Xu
Tong Zhang
FedML
34
38
0
09 Jun 2022
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning
Liam Collins
Hamed Hassani
Aryan Mokhtari
Sanjay Shakkottai
FedML
32
75
0
27 May 2022
Combating Client Dropout in Federated Learning via Friend Model
  Substitution
Combating Client Dropout in Federated Learning via Friend Model Substitution
Heqiang Wang
Jie Xu
FedML
23
5
0
26 May 2022
A Communication-Efficient Distributed Gradient Clipping Algorithm for
  Training Deep Neural Networks
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
Mingrui Liu
Zhenxun Zhuang
Yunwei Lei
Chunyang Liao
30
16
0
10 May 2022
FedNest: Federated Bilevel, Minimax, and Compositional Optimization
FedNest: Federated Bilevel, Minimax, and Compositional Optimization
Davoud Ataee Tarzanagh
Mingchen Li
Christos Thrampoulidis
Samet Oymak
FedML
40
73
0
04 May 2022
Data-heterogeneity-aware Mixing for Decentralized Learning
Data-heterogeneity-aware Mixing for Decentralized Learning
Yatin Dandi
Anastasia Koloskova
Martin Jaggi
Sebastian U. Stich
38
18
0
13 Apr 2022
Distributed Evolution Strategies for Black-box Stochastic Optimization
Distributed Evolution Strategies for Black-box Stochastic Optimization
Xiaoyu He
Zibin Zheng
Chuan Chen
Yuren Zhou
Chuan Luo
Qingwei Lin
24
4
0
09 Apr 2022
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial
  Participation
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation
Han Wang
Siddartha Marella
James Anderson
FedML
6
39
0
28 Mar 2022
Sparse Federated Learning with Hierarchical Personalized Models
Sparse Federated Learning with Hierarchical Personalized Models
Xiaofeng Liu
Qing Wang
Yunfeng Shao
Yinchuan Li
FedML
47
11
0
25 Mar 2022
Local Stochastic Factored Gradient Descent for Distributed Quantum State
  Tomography
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography
J. Kim
Taha Toghani
César A. Uribe
Anastasios Kyrillidis
27
3
0
22 Mar 2022
The Role of Local Steps in Local SGD
The Role of Local Steps in Local SGD
Tiancheng Qin
S. Rasoul Etesami
César A. Uribe
15
4
0
14 Mar 2022
Update Compression for Deep Neural Networks on the Edge
Update Compression for Deep Neural Networks on the Edge
Bo Chen
A. Bakhshi
Gustavo E. A. P. A. Batista
Brian Ng
Tat-Jun Chin
24
17
0
09 Mar 2022
On Federated Learning with Energy Harvesting Clients
On Federated Learning with Energy Harvesting Clients
Cong Shen
Jing Yang
Jie Xu
FedML
14
6
0
12 Feb 2022
Recycling Model Updates in Federated Learning: Are Gradient Subspaces
  Low-Rank?
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?
Sheikh Shams Azam
Seyyedali Hosseinalipour
Qiang Qiu
Christopher G. Brinton
FedML
20
20
0
01 Feb 2022
Communication-Efficient Consensus Mechanism for Federated Reinforcement
  Learning
Communication-Efficient Consensus Mechanism for Federated Reinforcement Learning
Xing Xu
Rongpeng Li
Zhifeng Zhao
Honggang Zhang
FedML
28
6
0
30 Jan 2022
Gradient Masked Averaging for Federated Learning
Gradient Masked Averaging for Federated Learning
Irene Tenison
Sai Aravind Sreeramadas
Vaikkunth Mugunthan
Edouard Oyallon
Irina Rish
Eugene Belilovsky
FedML
68
24
0
28 Jan 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
24
6
0
27 Jan 2022
Partial Model Averaging in Federated Learning: Performance Guarantees
  and Benefits
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits
Sunwoo Lee
Anit Kumar Sahu
Chaoyang He
Salman Avestimehr
FedML
25
16
0
11 Jan 2022
Federated Optimization of Smooth Loss Functions
Federated Optimization of Smooth Loss Functions
Ali Jadbabaie
A. Makur
Devavrat Shah
FedML
21
7
0
06 Jan 2022
Communication-Efficient Distributed SGD with Compressed Sensing
Communication-Efficient Distributed SGD with Compressed Sensing
Yujie Tang
V. Ramanathan
Junshan Zhang
Na Li
FedML
12
8
0
15 Dec 2021
Efficient and Reliable Overlay Networks for Decentralized Federated
  Learning
Efficient and Reliable Overlay Networks for Decentralized Federated Learning
Yifan Hua
Kevin Miller
Andrea L. Bertozzi
Chao Qian
Bao Wang
OOD
FedML
39
20
0
12 Dec 2021
Collaborative Learning over Wireless Networks: An Introductory Overview
Collaborative Learning over Wireless Networks: An Introductory Overview
Emre Ozfatura
Deniz Gunduz
H. Vincent Poor
22
11
0
07 Dec 2021
12345
Next