:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Qu, Zhaonan, Lin, Kaixiang, Li, Zhaojian, Zhou, Jiayu, Zhou, Zhengyuan
Formato:	Preprint
Publicado:	2020
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2007.05690
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

FedAvg-Based CTMC Hazard Model for Federated Bridge Deterioration Assessment
por: Yasuno, Takato
Publicado: (2026)

Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg
por: Jian, Like, et al.
Publicado: (2025)

Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training?
por: Chen, Shuxiao, et al.
Publicado: (2021)

Kuramoto-FedAvg: Using Synchronization Dynamics to Improve Federated Learning Optimization under Statistical Heterogeneity
por: Muhebwa, Aggrey, et al.
Publicado: (2025)

Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm
por: Hongjiao Wu
Publicado: (2024)

Achieving Linear Speedup for Composite Federated Learning
por: Huang, Kun, et al.
Publicado: (2026)

On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
por: Xiong, Guojun, et al.
Publicado: (2024)

FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning
por: Zhou, Yanbing, et al.
Publicado: (2025)

Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
por: Wang, Xiaolu, et al.
Publicado: (2024)

Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
por: Zheng, Zhong, et al.
Publicado: (2023)

FedNoisy: Federated Noisy Label Learning Benchmark
por: Liang, Siqi, et al.
Publicado: (2023)

FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
por: Zheng, Weiying, et al.
Publicado: (2025)

Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
por: Xie, Xingyu, et al.
Publicado: (2022)

FedHQ: Hybrid Runtime Quantization for Federated Learning
por: Zheng, Zihao, et al.
Publicado: (2025)

FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling
por: Wu, Zhengyu, et al.
Publicado: (2025)

FedGiA: An Efficient Hybrid Algorithm for Federated Learning
por: Zhou, Shenglong, et al.
Publicado: (2022)

FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
por: Abbasi, Ali, et al.
Publicado: (2024)

Distributionally Robust Instrumental Variables Estimation
por: Qu, Zhaonan, et al.
Publicado: (2024)

StatAvg: Mitigating Data Heterogeneity in Federated Learning for Intrusion Detection Systems
por: Bouzinis, Pavlos S., et al.
Publicado: (2024)

FedGTA: Topology-aware Averaging for Federated Graph Learning
por: Li, Xunkai, et al.
Publicado: (2024)

Nesterov-Accelerated Robust Federated Learning Over Byzantine Adversaries
por: Xu, Lihan, et al.
Publicado: (2025)

Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
por: Ganguly, Bhargav, et al.
Publicado: (2023)

EMA-Nesterov: Stabilizing Nesterov's Lookahead for Accelerated Deep Learning Optimization
por: Yau, Chung-Yiu, et al.
Publicado: (2026)

FedRGL: Robust Federated Graph Learning for Label Noise
por: Li, De, et al.
Publicado: (2024)

FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving
por: Kou, Wei-Bin, et al.
Publicado: (2025)

FedMerge: Federated Personalization via Model Merging
por: Chen, Shutong, et al.
Publicado: (2025)

A Unified Analysis for Finite Weight Averaging
por: Wang, Peng, et al.
Publicado: (2024)

FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
por: Li, Xingyu, et al.
Publicado: (2021)

Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data
por: Zhou, Tailin, et al.
Publicado: (2023)

FedUMM: A General Framework for Federated Learning with Unified Multimodal Models
por: Su, Zhaolong, et al.
Publicado: (2026)

FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization
por: Li, Hongze, et al.
Publicado: (2025)

UniFed: All-In-One Federated Learning Platform to Unify Open-Source Frameworks
por: Liu, Xiaoyuan, et al.
Publicado: (2022)

Lightweight and Robust Federated Data Valuation
por: Tang, Guojun, et al.
Publicado: (2025)

Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization
por: Guo, Luyao, et al.
Publicado: (2023)

Minibatch and Local SGD: Algorithmic Stability and Linear Speedup in Generalization
por: Lei, Yunwen, et al.
Publicado: (2023)

FedVeca: Federated Vectorized Averaging on Non-IID Data with Adaptive Bi-directional Global Objective
por: Luo, Ping, et al.
Publicado: (2022)

FedDW: Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning
por: Liu, Jiayu, et al.
Publicado: (2024)

FedADP: Unified Model Aggregation for Federated Learning with Heterogeneous Model Architectures
por: Wang, Jiacheng, et al.
Publicado: (2025)

On the Last-Iterate Convergence of Shuffling Gradient Methods
por: Liu, Zijian, et al.
Publicado: (2024)

Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
por: Liu, Zijian, et al.
Publicado: (2024)