Saved in:
| Main Authors: | Qu, Zhaonan, Lin, Kaixiang, Li, Zhaojian, Zhou, Jiayu, Zhou, Zhengyuan |
|---|---|
| Format: | Preprint |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2007.05690 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedAvg-Based CTMC Hazard Model for Federated Bridge Deterioration Assessment
by: Yasuno, Takato
Published: (2026)
by: Yasuno, Takato
Published: (2026)
Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg
by: Jian, Like, et al.
Published: (2025)
by: Jian, Like, et al.
Published: (2025)
Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training?
by: Chen, Shuxiao, et al.
Published: (2021)
by: Chen, Shuxiao, et al.
Published: (2021)
Kuramoto-FedAvg: Using Synchronization Dynamics to Improve Federated Learning Optimization under Statistical Heterogeneity
by: Muhebwa, Aggrey, et al.
Published: (2025)
by: Muhebwa, Aggrey, et al.
Published: (2025)
Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm
by: Hongjiao Wu
Published: (2024)
by: Hongjiao Wu
Published: (2024)
Achieving Linear Speedup for Composite Federated Learning
by: Huang, Kun, et al.
Published: (2026)
by: Huang, Kun, et al.
Published: (2026)
On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
by: Xiong, Guojun, et al.
Published: (2024)
by: Xiong, Guojun, et al.
Published: (2024)
FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning
by: Zhou, Yanbing, et al.
Published: (2025)
by: Zhou, Yanbing, et al.
Published: (2025)
Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
by: Wang, Xiaolu, et al.
Published: (2024)
by: Wang, Xiaolu, et al.
Published: (2024)
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
by: Zheng, Zhong, et al.
Published: (2023)
by: Zheng, Zhong, et al.
Published: (2023)
FedNoisy: Federated Noisy Label Learning Benchmark
by: Liang, Siqi, et al.
Published: (2023)
by: Liang, Siqi, et al.
Published: (2023)
FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
by: Zheng, Weiying, et al.
Published: (2025)
by: Zheng, Weiying, et al.
Published: (2025)
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
by: Xie, Xingyu, et al.
Published: (2022)
by: Xie, Xingyu, et al.
Published: (2022)
FedHQ: Hybrid Runtime Quantization for Federated Learning
by: Zheng, Zihao, et al.
Published: (2025)
by: Zheng, Zihao, et al.
Published: (2025)
FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
FedGiA: An Efficient Hybrid Algorithm for Federated Learning
by: Zhou, Shenglong, et al.
Published: (2022)
by: Zhou, Shenglong, et al.
Published: (2022)
FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
by: Abbasi, Ali, et al.
Published: (2024)
by: Abbasi, Ali, et al.
Published: (2024)
Distributionally Robust Instrumental Variables Estimation
by: Qu, Zhaonan, et al.
Published: (2024)
by: Qu, Zhaonan, et al.
Published: (2024)
StatAvg: Mitigating Data Heterogeneity in Federated Learning for Intrusion Detection Systems
by: Bouzinis, Pavlos S., et al.
Published: (2024)
by: Bouzinis, Pavlos S., et al.
Published: (2024)
FedGTA: Topology-aware Averaging for Federated Graph Learning
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
Nesterov-Accelerated Robust Federated Learning Over Byzantine Adversaries
by: Xu, Lihan, et al.
Published: (2025)
by: Xu, Lihan, et al.
Published: (2025)
Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
by: Ganguly, Bhargav, et al.
Published: (2023)
by: Ganguly, Bhargav, et al.
Published: (2023)
EMA-Nesterov: Stabilizing Nesterov's Lookahead for Accelerated Deep Learning Optimization
by: Yau, Chung-Yiu, et al.
Published: (2026)
by: Yau, Chung-Yiu, et al.
Published: (2026)
FedRGL: Robust Federated Graph Learning for Label Noise
by: Li, De, et al.
Published: (2024)
by: Li, De, et al.
Published: (2024)
FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving
by: Kou, Wei-Bin, et al.
Published: (2025)
by: Kou, Wei-Bin, et al.
Published: (2025)
FedMerge: Federated Personalization via Model Merging
by: Chen, Shutong, et al.
Published: (2025)
by: Chen, Shutong, et al.
Published: (2025)
A Unified Analysis for Finite Weight Averaging
by: Wang, Peng, et al.
Published: (2024)
by: Wang, Peng, et al.
Published: (2024)
FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
by: Li, Xingyu, et al.
Published: (2021)
by: Li, Xingyu, et al.
Published: (2021)
Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data
by: Zhou, Tailin, et al.
Published: (2023)
by: Zhou, Tailin, et al.
Published: (2023)
FedUMM: A General Framework for Federated Learning with Unified Multimodal Models
by: Su, Zhaolong, et al.
Published: (2026)
by: Su, Zhaolong, et al.
Published: (2026)
FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization
by: Li, Hongze, et al.
Published: (2025)
by: Li, Hongze, et al.
Published: (2025)
UniFed: All-In-One Federated Learning Platform to Unify Open-Source Frameworks
by: Liu, Xiaoyuan, et al.
Published: (2022)
by: Liu, Xiaoyuan, et al.
Published: (2022)
Lightweight and Robust Federated Data Valuation
by: Tang, Guojun, et al.
Published: (2025)
by: Tang, Guojun, et al.
Published: (2025)
Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization
by: Guo, Luyao, et al.
Published: (2023)
by: Guo, Luyao, et al.
Published: (2023)
Minibatch and Local SGD: Algorithmic Stability and Linear Speedup in Generalization
by: Lei, Yunwen, et al.
Published: (2023)
by: Lei, Yunwen, et al.
Published: (2023)
FedVeca: Federated Vectorized Averaging on Non-IID Data with Adaptive Bi-directional Global Objective
by: Luo, Ping, et al.
Published: (2022)
by: Luo, Ping, et al.
Published: (2022)
FedDW: Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning
by: Liu, Jiayu, et al.
Published: (2024)
by: Liu, Jiayu, et al.
Published: (2024)
FedADP: Unified Model Aggregation for Federated Learning with Heterogeneous Model Architectures
by: Wang, Jiacheng, et al.
Published: (2025)
by: Wang, Jiacheng, et al.
Published: (2025)
On the Last-Iterate Convergence of Shuffling Gradient Methods
by: Liu, Zijian, et al.
Published: (2024)
by: Liu, Zijian, et al.
Published: (2024)
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
by: Liu, Zijian, et al.
Published: (2024)
by: Liu, Zijian, et al.
Published: (2024)
Similar Items
-
FedAvg-Based CTMC Hazard Model for Federated Bridge Deterioration Assessment
by: Yasuno, Takato
Published: (2026) -
Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg
by: Jian, Like, et al.
Published: (2025) -
Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training?
by: Chen, Shuxiao, et al.
Published: (2021) -
Kuramoto-FedAvg: Using Synchronization Dynamics to Improve Federated Learning Optimization under Statistical Heterogeneity
by: Muhebwa, Aggrey, et al.
Published: (2025) -
Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm
by: Hongjiao Wu
Published: (2024)