:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Yipeng, Lyu, Xinchen
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2311.03154
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
by: Li, Yipeng, et al.
Published: (2024)

A Unified Analysis of Stochastic Gradient Descent with Arbitrary Data Permutations and Beyond
by: Li, Yipeng, et al.
Published: (2025)

Convergence Analysis of Split Federated Learning on Heterogeneous Data
by: Han, Pengchao, et al.
Published: (2024)

Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data
by: Liu, Jie, et al.
Published: (2025)

The Power of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacy
by: Ma, Jiating, et al.
Published: (2024)

Faster Convergence on Heterogeneous Federated Edge Learning: An Adaptive Clustered Data Sharing Approach
by: Hu, Gang, et al.
Published: (2024)

SplitFrozen: Split Learning with Device-side Model Frozen for Fine-Tuning LLM on Heterogeneous Resource-Constrained Devices
by: Ma, Jian, et al.
Published: (2025)

Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysis
by: Liang, Yipeng, et al.
Published: (2024)

Federated Online Learning for Heterogeneous Multisource Streaming Data
by: Li, Jingmao, et al.
Published: (2025)

Convergent Differential Privacy Analysis for General Federated Learning
by: Sun, Yan, et al.
Published: (2024)

On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments
by: Wang, Leo Muxing, et al.
Published: (2024)

Factor-Assisted Federated Learning for Personalized Optimization with Heterogeneous Data
by: Wang, Feifei, et al.
Published: (2023)

Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving
by: Kou, Wei-Bin, et al.
Published: (2024)

HeterCSI: Channel-Adaptive Heterogeneous CSI Pretraining Framework for Generalized Wireless Foundation Models
by: Zhang, Chenyu, et al.
Published: (2026)

Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis
by: Chen, Zhijie, et al.
Published: (2024)

The Impact Analysis of Delays in Asynchronous Federated Learning with Data Heterogeneity for Edge Intelligence
by: Hao, Ziruo, et al.
Published: (2025)

Mobility-Assisted Decentralized Federated Learning: Convergence Analysis and A Data-Driven Approach
by: Jahani, Reza, et al.
Published: (2025)

Convergence Guarantees for Federated SARSA with Local Training and Heterogeneous Agents
by: Mangold, Paul, et al.
Published: (2025)

Efficient Federated Learning with Encrypted Data Sharing for Data-Heterogeneous Edge Devices
by: Li, Hangyu, et al.
Published: (2025)

Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2025)

Data Heterogeneity and Forgotten Labels in Split Federated Learning
by: Tirana, Joana, et al.
Published: (2025)

Communication-Efficient Federated Learning With Data and Client Heterogeneity
by: Zakerinia, Hossein, et al.
Published: (2022)

Rethinking the initialization of Momentum in Federated Learning with Heterogeneous Data
by: Xiao, Chenguang, et al.
Published: (2024)

Dimensionality Reduction for Robust Federated Learning: A Theoretical Analysis and Convergence Guarantee
by: Zuo, Shiyuan, et al.
Published: (2026)

FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
by: Yang, Zhiqin, et al.
Published: (2025)

Similarity-based Label Inference Attack against Training and Inference of Split Learning
by: Liu, Junlin, et al.
Published: (2022)

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data
by: Zhu, Shuchen, et al.
Published: (2026)

Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression
by: Su, Xiaoxin, et al.
Published: (2024)

Federated Learning on Virtual Heterogeneous Data with Local-global Distillation
by: Huang, Chun-Yin, et al.
Published: (2023)

Analysis of Asynchronous Federated Learning: Unraveling the Interactions between Gradient Compression, Delay, and Data Heterogeneity
by: Yang, Diying, et al.
Published: (2025)

Personalized Federated Learning on Heterogeneous and Long-Tailed Data via Expert Collaborative Learning
by: Lv, Fengling, et al.
Published: (2024)

Tackling Data Heterogeneity in Federated Learning via Loss Decomposition
by: Zeng, Shuang, et al.
Published: (2024)

Client Selection in Federated Learning with Data Heterogeneity and Network Latencies
by: Vardhan, Harsh, et al.
Published: (2025)

Fisher-Informed Parameterwise Aggregation for Federated Learning with Heterogeneous Data
by: Chang, Zhipeng, et al.
Published: (2026)

On Global Convergence Rates for Federated Softmax Policy Gradient under Heterogeneous Environments
by: Labbi, Safwan, et al.
Published: (2025)

Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning
by: Li, Zhilong, et al.
Published: (2024)

Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations
by: Shao, Yumeng, et al.
Published: (2024)

On the Convergence of Federated Learning Algorithms without Data Similarity
by: Beikmohammadi, Ali, et al.
Published: (2024)

BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity
by: Guerra-Manzanares, Alejandro, et al.
Published: (2025)

Towards Robust Knowledge Removal in Federated Learning with High Data Heterogeneity
by: Santi, Riccardo, et al.
Published: (2025)