Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning

8 March 2021

Papers citing "Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning"

44 / 44 papers shown

Title
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning Chengui Xiao Songbai Liu FedML 72 0 0 29 Apr 2025
Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data Jie Liu Yishuo Wang FedML 80 0 0 20 Mar 2025
Drift-Aware Federated Learning: A Causal Perspective Yunjie Fang Sheng Wu Tao Yang X. Wu Bo Hu FedML 55 0 0 13 Mar 2025
Diffusion Model-Based Data Synthesis Aided Federated Semi-Supervised Learning Zhongwei Wang Tong Wu Zhiyong Chen Liang Qian Yin Xu Meixia Tao FedML 36 0 0 04 Jan 2025
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs Yan Sun Li Shen Dacheng Tao FedML 25 0 0 27 Sep 2024
One-Shot Federated Learning with Bayesian Pseudocoresets Tim d'Hondt Mykola Pechenizkiy Robert Peharz FedML 37 0 0 04 Jun 2024
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments Han Wang Sihong He Zhili Zhang Fei Miao James Anderson 51 3 0 29 May 2024
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler Hongyi Peng Han Yu Xiaoli Tang Xiaoxiao Li 47 3 0 24 May 2024
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning Chenyu Zhang Han Wang Aritra Mitra James Anderson 34 18 0 27 Jan 2024
Leveraging Function Space Aggregation for Federated Learning at Scale Nikita Dhawan Nicole Mitchell Zachary B. Charles Zachary Garrett Gintare Karolina Dziugaite FedML 24 3 0 17 Nov 2023
Federated Learning with Manifold Regularization and Normalized Update Reaggregation Xuming An Li Shen Han Hu Yong Luo FedML 44 4 0 10 Nov 2023
Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models Zihao Lin Yan Sun Yifan Shi Xueqian Wang Lifu Huang Li Shen Dacheng Tao 34 11 0 04 Oct 2023
FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data Hao Sun Li Shen Shi-Yong Chen Jingwei Sun Jing Li Guangzhong Sun Dacheng Tao FedML 45 1 0 18 Sep 2023
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning Zebang Shen Jiayuan Ye Anmin Kang Hamed Hassani Reza Shokri FedML 34 16 0 11 Sep 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Zachary B. Charles Nicole Mitchell Krishna Pillutla Michael Reneer Zachary Garrett FedML AI4CE 36 28 0 18 Jul 2023
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators Sikai Bai Shuaicheng Li Weiming Zhuang Jie Zhang Song Guo Kunlin Yang Jun Hou Shuai Zhang Junyu Gao Shuai Yi FedML 26 6 0 11 Jul 2023
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization Yan Sun Li Shen Dacheng Tao FedML 20 14 0 09 Jun 2023
On First-Order Meta-Reinforcement Learning with Moreau Envelopes Taha Toghani Sebastian Perez-Salazar César A. Uribe 29 2 0 20 May 2023
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape Yan Sun Li Shen Shi-Yong Chen Liang Ding Dacheng Tao FedML 34 33 0 19 May 2023
Faster Federated Learning with Decaying Number of Local SGD Steps Jed Mills Jia Hu Geyong Min FedML 30 7 0 16 May 2023
SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training Riyasat Ohib Bishal Thapaliya Pratyush Gaggenapalli Jiaheng Liu Vince D. Calhoun Sergey Plis FedML 21 2 0 15 Apr 2023
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy Yan Sun Li Shen Tiansheng Huang Liang Ding Dacheng Tao FedML 36 51 0 21 Feb 2023
Federated Gradient Matching Pursuit Halyun Jeong Deanna Needell Jing Qin FedML 37 1 0 20 Feb 2023
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 Automatic Differentiation Keith Rush Zachary B. Charles Zachary Garrett FedML 34 1 0 18 Jan 2023
PersA-FL: Personalized Asynchronous Federated Learning Taha Toghani Soomin Lee César A. Uribe FedML 34 6 0 03 Oct 2022
Federated Learning with Label Distribution Skew via Logits Calibration Jie M. Zhang Zhiqi Li Bo-wen Li Jianghe Xu Shuang Wu Shouhong Ding Chao Wu FedML 21 140 0 01 Sep 2022
Motley: Benchmarking Heterogeneity and Personalization in Federated Learning Shan-shan Wu Tian Li Zachary B. Charles Yu Xiao Ziyu Liu Zheng Xu Virginia Smith FedML 40 44 0 18 Jun 2022
Federated Learning on Riemannian Manifolds Jiaxiang Li Shiqian Ma FedML 13 13 0 12 Jun 2022
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 Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML 32 75 0 27 May 2022
FL_PyTorch: optimization research simulator for federated learning Konstantin Burlachenko Samuel Horváth Peter Richtárik FedML 45 18 0 07 Feb 2022
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning Elnur Gasanov Ahmed Khaled Samuel Horváth Peter Richtárik FedML 30 16 0 22 Nov 2021
Exploiting Heterogeneity in Robust Federated Best-Arm Identification A. Mitra Hamed Hassani George Pappas FedML 31 26 0 13 Sep 2021
Iterated Vector Fields and Conservatism, with Applications to Federated Learning Zachary B. Charles Keith Rush 27 6 0 08 Sep 2021
Accelerating Federated Learning with a Global Biased Optimiser Jed Mills Jia Hu Geyong Min Rui Jin Siwei Zheng Jin Wang FedML AI4CE 34 9 0 20 Aug 2021
An Operator Splitting View of Federated Learning Saber Malekmohammadi K. Shaloudegi Zeou Hu Yaoliang Yu FedML 26 2 0 12 Aug 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
A Non-parametric View of FedAvg and FedProx: Beyond Stationary Points Lili Su Jiaming Xu Pengkun Yang FedML 14 13 0 29 Jun 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 21 113 0 15 Jun 2021
Local Adaptivity in Federated Learning: Convergence and Consistency Jianyu Wang Zheng Xu Zachary Garrett Zachary B. Charles Luyang Liu Gauri Joshi FedML 26 39 0 04 Jun 2021
FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization Quoc Tran-Dinh Nhan H. Pham Dzung Phan Lam M. Nguyen FedML 18 39 0 05 Mar 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 341 11,684 0 09 Mar 2017