SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

14 October 2019

Sai Praneeth Karimireddy

Papers citing "SCAFFOLD: Stochastic Controlled Averaging for Federated Learning"

50 / 80 papers shown

Title
Ranking-Based At-Risk Student Prediction Using Federated Learning and Differential Features Shunsuke Yoneda Valdemar Švábenský Gen Li Daisuke Deguchi Atsushi Shimada 29 0 0 14 May 2025
Towards One-shot Federated Learning: Advances, Challenges, and Future Directions Flora Amato Lingyu Qiu Mohammad Tanveer S. Cuomo F. Giampaolo F. Piccialli FedML 63 0 0 05 May 2025
Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning Yanbiao Ma Wei-Ming Dai Wenke Huang Jiayi Chen 105 0 0 09 Mar 2025
Federated Learning with Reservoir State Analysis for Time Series Anomaly Detection Keigo Nogami Tamura Hiroto Gouhei Tanaka FedML 85 0 0 17 Feb 2025
Aggregating Low Rank Adapters in Federated Fine-tuning Evelyn Trautmann Ian Hales Martin F. Volk AI4CE FedML 39 0 0 10 Jan 2025
On the Impact of Data Heterogeneity in Federated Learning Environments with Application to Healthcare Networks Usevalad Milasheuski Bernardo Camajori Tedeschini M. Nicoli S. Savazzi OOD 20 5 0 29 Apr 2024
Apodotiko: Enabling Efficient Serverless Federated Learning in Heterogeneous Environments Mohak Chadha Alexander Jensen Jianfeng Gu Osama Abboud Michael Gerndt 31 0 0 22 Apr 2024
Distributed Personalized Empirical Risk Minimization Yuyang Deng Mohammad Mahdi Kamani Pouria Mahdavinia M. Mahdavi 31 4 0 26 Oct 2023
Neural Collapse Inspired Federated Learning with Non-iid Data Chenxi Huang Liang Xie Yibo Yang Wenxiao Wang Binbin Lin D. Cai FedML 34 3 0 27 Mar 2023
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI Juexiao Zhou Longxi Zhou Di Wang Xiaopeng Xu Haoyang Li Yuetan Chu Wenkai Han Xin Gao 28 20 0 20 Feb 2023
On the Convergence of Federated Averaging with Cyclic Client Participation Yae Jee Cho Pranay Sharma Gauri Joshi Zheng Xu Satyen Kale Tong Zhang FedML 44 27 0 06 Feb 2023
Toward Data Heterogeneity of Federated Learning Yuchuan Huang Chen Hu FedML 30 1 0 17 Dec 2022
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge Yaxin Luopan Rui Han Qinglong Zhang Chi Harold Liu Guoren Wang FedML 26 18 0 04 Dec 2022
DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi Weizhong Zhang Yueqi Xie Jiahui Gao Xiaoyu Wang Sunghun Kim Qifeng Chen DD 39 26 0 20 Nov 2022
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity A. Maranjyan M. Safaryan Peter Richtárik 34 13 0 28 Oct 2022
FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings Junyi Li Heng-Chiao Huang FedML 24 6 0 25 Oct 2022
Federated Learning with Privacy-Preserving Ensemble Attention Distillation Xuan Gong Liangchen Song Rishi Vedula Abhishek Sharma Meng Zheng ... Arun Innanje Terrence Chen Junsong Yuan David Doermann Ziyan Wu FedML 23 27 0 16 Oct 2022
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao Kai Yang Dongjin Song 27 11 0 14 Oct 2022
On the Stability Analysis of Open Federated Learning Systems Youbang Sun H. Fernando Tianyi Chen Shahin Shahrampour FedML 29 1 0 25 Sep 2022
Multi-Level Branched Regularization for Federated Learning Jinkyu Kim Geeho Kim Bohyung Han FedML 22 53 0 14 Jul 2022
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning Daoyuan Chen Dawei Gao Weirui Kuang Yaliang Li Bolin Ding FedML 30 63 0 08 Jun 2022
An Optimal Transport Approach to Personalized Federated Learning Farzan Farnia Amirhossein Reisizadeh Ramtin Pedarsani Ali Jadbabaie OT OOD FedML 31 12 0 06 Jun 2022
Straggler-Resilient Personalized Federated Learning Isidoros Tziotis Zebang Shen Ramtin Pedarsani Hamed Hassani Aryan Mokhtari FedML 33 9 0 05 Jun 2022
A Fair Federated Learning Framework With Reinforcement Learning Yaqi Sun Shijing Si Jianzong Wang Yuhan Dong Z. Zhu Jing Xiao FedML 13 7 0 26 May 2022
Federated Random Reshuffling with Compression and Variance Reduction Grigory Malinovsky Peter Richtárik FedML 27 10 0 08 May 2022
Uncertainty Minimization for Personalized Federated Semi-Supervised Learning Yanhang Shi Siguang Chen Haijun Zhang FedML 23 8 0 05 May 2022
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction Junyi Li Feihu Huang Heng-Chiao Huang FedML 19 27 0 03 May 2022
Data-heterogeneity-aware Mixing for Decentralized Learning Yatin Dandi Anastasia Koloskova Martin Jaggi Sebastian U. Stich 38 18 0 13 Apr 2022
Deep Class Incremental Learning from Decentralized Data Xiaohan Zhang Songlin Dong Jinjie Chen Qiaoling Tian Yihong Gong Xiaopeng Hong CLL 28 11 0 11 Mar 2022
FedCAT: Towards Accurate Federated Learning via Device Concatenation Ming Hu Tian Liu Zhiwei Ling Zhihao Yue Mingsong Chen FedML 21 1 0 23 Feb 2022
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data Isha Garg M. Nagaraj Kaushik Roy FedML 31 1 0 21 Jan 2022
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images Meirui Jiang Zirui Wang Qi Dou FedML 33 123 0 20 Dec 2021
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig AI4CE 37 25 0 15 Dec 2021
Efficient Federated Learning for AIoT Applications Using Knowledge Distillation Tian Liu Xian Wei Jun Xia Xin Fu Ting Wang Mingsong Chen 6 15 0 29 Nov 2021
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning Yuezhou Wu Yan Kang Jiahuan Luo Yuanqin He Qiang Yang FedML AAML 19 69 0 16 Nov 2021
Towards Model Agnostic Federated Learning Using Knowledge Distillation A. Afonin Sai Praneeth Karimireddy FedML 30 44 0 28 Oct 2021
A Stochastic Newton Algorithm for Distributed Convex Optimization Brian Bullins Kumar Kshitij Patel Ohad Shamir Nathan Srebro Blake E. Woodworth 28 15 0 07 Oct 2021
Federated Feature Selection for Cyber-Physical Systems of Systems P. Cassará A. Gotta Lorenzo Valerio 20 35 0 23 Sep 2021
Connecting Low-Loss Subspace for Personalized Federated Learning S. Hahn Minwoo Jeong Junghye Lee FedML 24 18 0 16 Sep 2021
FedJAX: Federated learning simulation with JAX Jae Hun Ro A. Suresh Ke Wu FedML 33 48 0 04 Aug 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 33 77 0 05 Jun 2021
Local Adaptivity in Federated Learning: Convergence and Consistency Jianyu Wang Zheng Xu Zachary Garrett Zachary B. Charles Luyang Liu Gauri Joshi FedML 32 39 0 04 Jun 2021
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning Minxue Tang Xuefei Ning Yitu Wang Jingwei Sun Yu Wang H. Li Yiran Chen FedML 27 80 0 24 Mar 2021
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning Zachary B. Charles Jakub Konecný FedML 26 63 0 08 Mar 2021
Personalized Federated Learning using Hypernetworks Aviv Shamsian Aviv Navon Ethan Fetaya Gal Chechik FedML 41 324 0 08 Mar 2021
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency Yuyang Deng M. Mahdavi 30 58 0 25 Feb 2021
Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks Jie Xu Heqiang Wang Lixing Chen FedML 56 43 0 10 Jan 2021
Optimising cost vs accuracy of decentralised analytics in fog computing environments Lorenzo Valerio A. Passarella M. Conti 32 1 0 09 Dec 2020
Local SGD: Unified Theory and New Efficient Methods Eduard A. Gorbunov Filip Hanzely Peter Richtárik FedML 35 109 0 03 Nov 2020
Optimal Client Sampling for Federated Learning Wenlin Chen Samuel Horváth Peter Richtárik FedML 42 190 0 26 Oct 2020