Projects
Reading
People
Chat
SU\G
(𝔸)
/K·U
Projects
Reading
People
Chat
Sign Up
Light
Dark
System
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data.
Xinwei Zhang
,
Mingyi Hong
,
Sairaj V. Dhople
,
Wotao Yin
,
Yang Liu
Type:
Preprint
Publication Date:
2020-05-22
Citations:
54
View Publication
Share
Locations
arXiv (Cornell University) -
View
Similar Works
Action
Title
Year
Authors
+
PDF
Chat
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data
2021
Xinwei Zhang
Mingyi Hong
Sairaj V. Dhople
Wotao Yin
Yang Liu
+
A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg
2020
Zhaonan Qu
Kaixiang Lin
Zhaojian Li
Jiayu Zhou
Zhengyuan Zhou
+
PDF
Chat
A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg
2023
Zhaonan Qu
Kaixiang Lin
Zhaojian Li
Jiayu Zhou
Zhengyuan Zhou
+
Federated Learning's Blessing: FedAvg has Linear Speedup
2021
Zhaonan Qu
Kaixiang Lin
Zhaojian Li
Jiayu Zhou
Zhengyuan Zhou
+
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
2020
Farzin Haddadpour
Mohammad Mahdi Kamani
Aryan Mokhtari
Mehrdad Mahdavi
+
FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging
2023
Junyi Li
Feihu Huang
Heng Huang
+
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
2020
Farzin Haddadpour
Mohammad Mahdi Kamani
Aryan Mokhtari
Mehrdad Mahdavi
+
DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime
2023
Jong-Ho Park
Jinchao Xu
+
Federated Composite Optimization
2020
Honglin Yuan
Manzil Zaheer
Sashank J. Reddi
+
PDF
Chat
Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
2024
Xiaolu Wang
Zijian Li
Shi Jin
Jun Zhang
+
Locally Adaptive Federated Learning via Stochastic Polyak Stepsizes
2023
Sohom Mukherjee
Nicolas Loizou
Sebastian U. Stich
+
FedAgg: Adaptive Federated Learning with Aggregated Gradients
2023
Wenhao Yuan
Xuehe Wang
+
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
2021
Xinran Gu
Kaixuan Huang
Jingzhao Zhang
Longbo Huang
+
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
2021
Xinran Gu
Kaixuan Huang
Jingzhao Zhang
Longbo Huang
+
PDF
Chat
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
2021
Xinran Gu
Kaixuan Huang
Jingzhao Zhang
Longbo Huang
+
FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
2021
Xingyu Li
Zhe Qu
Bo Tang
Zhuo Lu
+
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients
2021
Aritra Mitra
Rayana H. Jaafar
George J. Pappas
Hamed Hassani
+
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients
2021
Aritra Mitra
Rayana H. Jaafar
George J. Pappas
Hamed Hassani
+
PDF
Chat
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization
2023
Huiming Chen
Huandong Wang
Quanming Yao
Yong Li
Depeng Jin
Qiang Yang
+
PDF
Chat
Federated Optimization Under Intermittent Client Availability
2024
Yikai Yan
Chaoyue Niu
Yucheng Ding
Zhenzhe Zheng
Shaojie Tang
Qinya Li
Fan Wu
Chengfei Lyu
Yanghe Feng
Guihai Chen
Works That Cite This (38)
Action
Title
Year
Authors
+
Federated Composite Optimization
2020
Honglin Yuan
Manzil Zaheer
Sashank J. Reddi
+
FedCM: Federated Learning with Client-level Momentum
2021
Jing Xu
Sen Wang
Liwei Wang
Andrew Chi-Chih Yao
+
Local Adaptivity in Federated Learning: Convergence and Consistency
2021
Jianyu Wang
Zheng Xu
Zach Garrett
Zachary Charles
Luyang Liu
Gauri Joshi
+
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
2021
Raed Al Kontar
Naichen Shi
Xubo Yue
Seokhyun Chung
Eunshin Byon
Mosharaf Chowdhury
Judy Jin
Wissam Kontar
Neda Masoud
Maher Noueihed
+
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
2020
Farzin Haddadpour
Mohammad Mahdi Kamani
Aryan Mokhtari
Mehrdad Mahdavi
+
PDF
Chat
Faster Adaptive Federated Learning
2023
Xidong Wu
Feihu Huang
Zhengmian Hu
Heng Huang
+
The Internet of Federated Things (IoFT)
2021
Raed Al Kontar
Naichen Shi
Xubo Yue
Seokhyun Chung
Eunshin Byon
Mosharaf Chowdhury
Jionghua Jin
Wissam Kontar
Neda Masoud
Maher Nouiehed
+
PDF
Chat
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
2021
Xiaoxiao Li
Meirui Jiang
Xiaofei Zhang
Michael Kamp
Qi Dou
+
A Field Guide to Federated Optimization
2021
Jianyu Wang
Zachary Charles
Zheng Xu
Gauri Joshi
H. Brendan McMahan
Blaise Agüera y Arcas
Maruan Al-Shedivat
Galen Andrew
Salman Avestimehr
Katharine Daly
+
PDF
Chat
Bayesian Federated Neural Matching That Completes Full Information
2023
Peng Xiao
Samuel Cheng
Works Cited by This (25)
Action
Title
Year
Authors
+
PDF
Chat
Penalized likelihood regression for generalized linear models with non-quadratic penalties
2009
Anestis Antoniadis
Irène Gijbels
Mila Nikolova
+
Federated Learning: Strategies for Improving Communication Efficiency
2016
Jakub Konečný
H. Brendan McMahan
Felix X. Yu
Peter Richtárik
Ananda Theertha Suresh
Dave Bacon
+
Optimal algorithms for smooth and strongly convex distributed optimization in networks
2017
Kevin G. Seaman
Francis Bach
Sébastien Bubeck
Yin Tat Lee
Laurent Massoulié
+
When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning
2018
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
Kin K. Leung
Christian Makaya
Ting He
Kevin Chan
+
Distributed Non-Convex First-Order Optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms
2019
Haoran Sun
Mingyi Hong
+
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms
2018
Jianyu Wang
Gauri Joshi
+
PDF
Chat
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
2019
Hao Yu
Sen Yang
Shenghuo Zhu
+
LEAF: A Benchmark for Federated Settings
2018
Sebastian Caldas
Peter Wu
Li Tian
Jakub Konečný
H. Brendan McMahan
Virginia Smith
Ameet Talwalkar
+
On the Convergence of Federated Optimization in Heterogeneous Networks.
2018
Anit Kumar Sahu
Tian Li
Maziar Sanjabi
Manzil Zaheer
Ameet Talwalkar
Virginia Smith
+
Towards Federated Learning at Scale: System Design
2019
Keith Bonawitz
Hubert Eichner
Wolfgang Grieskamp
Dzmitry Huba
Alex Ingerman
Vladimir Ivanov
Chloé Kiddon
Jakub Konečný
Stefano Mazzocchi
H. Brendan McMahan