Saved in:
| Main Authors: | Zhang, Kai, Dai, Yutong, Wang, Hongyi, Xing, Eric, Chen, Xun, Sun, Lichao |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2303.04887 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Variational Bayes for Federated Continual Learning
by: Yao, Dezhong, et al.
Published: (2024)
by: Yao, Dezhong, et al.
Published: (2024)
Class-wise Federated Unlearning: Harnessing Active Forgetting with Teacher-Student Memory Generation
by: Li, Yuyuan, et al.
Published: (2023)
by: Li, Yuyuan, et al.
Published: (2023)
MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
by: Liu, Yuxi, et al.
Published: (2025)
by: Liu, Yuxi, et al.
Published: (2025)
FedNAR: Federated Optimization with Normalized Annealing Regularization
by: Li, Junbo, et al.
Published: (2023)
by: Li, Junbo, et al.
Published: (2023)
Rethinking LoRA for Data Heterogeneous Federated Learning: Subspace and State Alignment
by: Peng, Hongyi, et al.
Published: (2026)
by: Peng, Hongyi, et al.
Published: (2026)
SMoFi: Step-wise Momentum Fusion for Split Federated Learning on Heterogeneous Data
by: Yang, Mingkun, et al.
Published: (2025)
by: Yang, Mingkun, et al.
Published: (2025)
NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel
by: Thompson, Gabriel, et al.
Published: (2024)
by: Thompson, Gabriel, et al.
Published: (2024)
FedCAP: Robust Federated Learning via Customized Aggregation and Personalization
by: Li, Youpeng, et al.
Published: (2024)
by: Li, Youpeng, et al.
Published: (2024)
Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation
by: Ma, Xing
Published: (2025)
by: Ma, Xing
Published: (2025)
Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise
by: Liu, Yixin, et al.
Published: (2023)
by: Liu, Yixin, et al.
Published: (2023)
Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization
by: Zhang, Xinyu, et al.
Published: (2023)
by: Zhang, Xinyu, et al.
Published: (2023)
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
by: Zhang, Ke, et al.
Published: (2024)
by: Zhang, Ke, et al.
Published: (2024)
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
by: Wang, Ziyao, et al.
Published: (2024)
by: Wang, Ziyao, et al.
Published: (2024)
FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection
by: He, Yutong, et al.
Published: (2026)
by: He, Yutong, et al.
Published: (2026)
Federated Reinforcement Learning with Constraint Heterogeneity
by: Jin, Hao, et al.
Published: (2024)
by: Jin, Hao, et al.
Published: (2024)
STAGE: Tackling Semantic Drift in Multimodal Federated Graph Learning
by: Chen, Zekai, et al.
Published: (2026)
by: Chen, Zekai, et al.
Published: (2026)
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting
by: Dai, Rong, et al.
Published: (2024)
by: Dai, Rong, et al.
Published: (2024)
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination
by: Hu, Ming, et al.
Published: (2023)
by: Hu, Ming, et al.
Published: (2023)
Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning
by: Ye, Tiandi, et al.
Published: (2025)
by: Ye, Tiandi, et al.
Published: (2025)
HeTa: Relation-wise Heterogeneous Graph Foundation Attack Model
by: Wang, Yuling, et al.
Published: (2025)
by: Wang, Yuling, et al.
Published: (2025)
FedEL: Federated Elastic Learning for Heterogeneous Devices
by: Zhang, Letian, et al.
Published: (2025)
by: Zhang, Letian, et al.
Published: (2025)
Decentralized Federated Learning: A Survey and Perspective
by: Yuan, Liangqi, et al.
Published: (2023)
by: Yuan, Liangqi, et al.
Published: (2023)
Fusing Models with Complementary Expertise
by: Wang, Hongyi, et al.
Published: (2023)
by: Wang, Hongyi, et al.
Published: (2023)
GPU-Fuzz: Finding Memory Errors in Deep Learning Frameworks
by: Li, Zihao, et al.
Published: (2026)
by: Li, Zihao, et al.
Published: (2026)
Hypernetworks for Model-Heterogeneous Personalized Federated Learning
by: Zhang, Chen, et al.
Published: (2025)
by: Zhang, Chen, et al.
Published: (2025)
Beyond performance-wise Contribution Evaluation in Federated Learning
by: Pejo, Balazs
Published: (2026)
by: Pejo, Balazs
Published: (2026)
Heterogeneity-Oblivious Robust Federated Learning
by: Zhang, Weiyao, et al.
Published: (2025)
by: Zhang, Weiyao, et al.
Published: (2025)
FedMood: Federated Learning on Mobile Health Data for Mood Detection
by: Xu, Xiaohang, et al.
Published: (2021)
by: Xu, Xiaohang, et al.
Published: (2021)
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
by: Shi, Changlong, et al.
Published: (2025)
by: Shi, Changlong, et al.
Published: (2025)
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
by: Kim, Jisoo, et al.
Published: (2025)
by: Kim, Jisoo, et al.
Published: (2025)
Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training
by: Wu, Yebo, et al.
Published: (2024)
by: Wu, Yebo, et al.
Published: (2024)
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting
by: Tian, Chunlin, et al.
Published: (2024)
by: Tian, Chunlin, et al.
Published: (2024)
Generative Learning of Heterogeneous Tail Dependence
by: Sun, Xiangqian, et al.
Published: (2020)
by: Sun, Xiangqian, et al.
Published: (2020)
Modeling Inter-Intra Heterogeneity for Graph Federated Learning
by: Yu, Wentao, et al.
Published: (2024)
by: Yu, Wentao, et al.
Published: (2024)
Heterogeneity-Aware Knowledge Sharing for Graph Federated Learning
by: Yu, Wentao, et al.
Published: (2026)
by: Yu, Wentao, et al.
Published: (2026)
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness
by: Zhu, Shengkun, et al.
Published: (2024)
by: Zhu, Shengkun, et al.
Published: (2024)
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents
by: Labbi, Safwan, et al.
Published: (2024)
by: Labbi, Safwan, et al.
Published: (2024)
$γ$-FedHT: Stepsize-Aware Hard-Threshold Gradient Compression in Federated Learning
by: Lu, Rongwei, et al.
Published: (2025)
by: Lu, Rongwei, et al.
Published: (2025)
CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
by: Xing, Ke, et al.
Published: (2025)
by: Xing, Ke, et al.
Published: (2025)
Resource-efficient Layer-wise Federated Self-supervised Learning
by: Tun, Ye Lin, et al.
Published: (2024)
by: Tun, Ye Lin, et al.
Published: (2024)
Similar Items
-
Variational Bayes for Federated Continual Learning
by: Yao, Dezhong, et al.
Published: (2024) -
Class-wise Federated Unlearning: Harnessing Active Forgetting with Teacher-Student Memory Generation
by: Li, Yuyuan, et al.
Published: (2023) -
MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
by: Liu, Yuxi, et al.
Published: (2025) -
FedNAR: Federated Optimization with Normalized Annealing Regularization
by: Li, Junbo, et al.
Published: (2023) -
Rethinking LoRA for Data Heterogeneous Federated Learning: Subspace and State Alignment
by: Peng, Hongyi, et al.
Published: (2026)