Improving LoRA in Privacy-preserving Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Sun, Youbang, Li, Zitao, Li, Yaliang, Ding, Bolin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
by: Liu, Jianmin, et al.
Published: (2025)
by: Liu, Jianmin, et al.
Published: (2025)
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation
by: Xia, Tong, et al.
Published: (2023)
by: Xia, Tong, et al.
Published: (2023)
Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
by: Zhang, Baolei, et al.
Published: (2025)
by: Zhang, Baolei, et al.
Published: (2025)
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation
by: Xu, Jie, et al.
Published: (2024)
by: Xu, Jie, et al.
Published: (2024)
IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
by: Riya, Farhin Farhad, et al.
Published: (2026)
by: Riya, Farhin Farhad, et al.
Published: (2026)
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
by: Xing, Zhibo, et al.
Published: (2024)
by: Xing, Zhibo, et al.
Published: (2024)
Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
by: Shankar, Aditya, et al.
Published: (2024)
by: Shankar, Aditya, et al.
Published: (2024)
Differentially Private Federated Learning With Time-Adaptive Privacy Spending
by: Kiani, Shahrzad, et al.
Published: (2025)
by: Kiani, Shahrzad, et al.
Published: (2025)
Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning
by: Hosain, Md. Tanzib, et al.
Published: (2025)
by: Hosain, Md. Tanzib, et al.
Published: (2025)
Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach
by: Talaei, Mahtab, et al.
Published: (2024)
by: Talaei, Mahtab, et al.
Published: (2024)
Enhancing Federated Learning with Adaptive Differential Privacy and Priority-Based Aggregation
by: Talaei, Mahtab, et al.
Published: (2024)
by: Talaei, Mahtab, et al.
Published: (2024)
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
by: Kang, Tianqu, et al.
Published: (2024)
by: Kang, Tianqu, et al.
Published: (2024)
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)
by: Xu, Zhangchen, et al.
Published: (2024)
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives
by: Wang, Linlin, et al.
Published: (2024)
by: Wang, Linlin, et al.
Published: (2024)
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service
by: Liu, Yu, et al.
Published: (2024)
by: Liu, Yu, et al.
Published: (2024)
Detect \& Score: Privacy-Preserving Misbehaviour Detection and Contribution Evaluation in Federated Learning
by: Xhemrishi, Marvin, et al.
Published: (2025)
by: Xhemrishi, Marvin, et al.
Published: (2025)
A Lightweight Federated Learning Approach for Privacy-Preserving Botnet Detection in IoT
by: Mahmoud, Taha M., et al.
Published: (2025)
by: Mahmoud, Taha M., et al.
Published: (2025)
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
by: Kang, Yan, et al.
Published: (2022)
by: Kang, Yan, et al.
Published: (2022)
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
by: Yan, Bo, et al.
Published: (2023)
by: Yan, Bo, et al.
Published: (2023)
zkFL-Health: Blockchain-Enabled Zero-Knowledge Federated Learning for Medical AI Privacy
by: Sharma, Savvy, et al.
Published: (2025)
by: Sharma, Savvy, et al.
Published: (2025)
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model
by: Wu, Feijie, et al.
Published: (2024)
by: Wu, Feijie, et al.
Published: (2024)
UNIDEAL: Curriculum Knowledge Distillation Federated Learning
by: Yang, Yuwen, et al.
Published: (2023)
by: Yang, Yuwen, et al.
Published: (2023)
Foundation Models in Federated Learning: Assessing Backdoor Vulnerabilities
by: Li, Xi, et al.
Published: (2024)
by: Li, Xi, et al.
Published: (2024)
Federated Graph Learning with Adaptive Importance-based Sampling
by: Li, Anran, et al.
Published: (2024)
by: Li, Anran, et al.
Published: (2024)
Hear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning
by: Wang, Fei, et al.
Published: (2025)
by: Wang, Fei, et al.
Published: (2025)
Toward Malicious Clients Detection in Federated Learning
by: Dou, Zhihao, et al.
Published: (2025)
by: Dou, Zhihao, et al.
Published: (2025)
PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025)
by: Zhang, Hongliang, et al.
Published: (2025)
Random Client Selection on Contrastive Federated Learning for Tabular Data
by: Ginanjar, Achmad, et al.
Published: (2025)
by: Ginanjar, Achmad, et al.
Published: (2025)
Federated Multi-Task Learning on Non-IID Data Silos: An Experimental Study
by: Yang, Yuwen, et al.
Published: (2024)
by: Yang, Yuwen, et al.
Published: (2024)
TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems
by: Di Gennaro, Marco, et al.
Published: (2025)
by: Di Gennaro, Marco, et al.
Published: (2025)
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
by: Li, Zilinghan, et al.
Published: (2024)
by: Li, Zilinghan, et al.
Published: (2024)
Find a Scapegoat: Poisoning Membership Inference Attack and Defense to Federated Learning
by: Mo, Wenjin, et al.
Published: (2025)
by: Mo, Wenjin, et al.
Published: (2025)
Protecting Confidentiality, Privacy and Integrity in Collaborative Learning
by: Chen, Dong, et al.
Published: (2024)
by: Chen, Dong, et al.
Published: (2024)
Balancing Privacy, Robustness, and Efficiency in Machine Learning
by: Allouah, Youssef, et al.
Published: (2023)
by: Allouah, Youssef, et al.
Published: (2023)
Privacy-preserving quantum federated learning via gradient hiding
by: Li, Changhao, et al.
Published: (2023)
by: Li, Changhao, et al.
Published: (2023)
FedPDD: A Privacy-preserving Double Distillation Framework for Cross-silo Federated Recommendation
by: Wan, Sheng, et al.
Published: (2023)
by: Wan, Sheng, et al.
Published: (2023)
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach
by: Tan, Qi, et al.
Published: (2024)
by: Tan, Qi, et al.
Published: (2024)
Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning
by: Yang, Hansi, et al.
Published: (2024)
by: Yang, Hansi, et al.
Published: (2024)
Towards Trustworthy Federated Learning
by: Basharat, Alina, et al.
Published: (2025)
by: Basharat, Alina, et al.
Published: (2025)
LoRA-based Parameter-Efficient LLMs for Continuous Learning in Edge-based Malware Detection
by: Rondanini, Christian, et al.
Published: (2026)
by: Rondanini, Christian, et al.
Published: (2026)
Similar Items
-
SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
by: Liu, Jianmin, et al.
Published: (2025) -
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation
by: Xia, Tong, et al.
Published: (2023) -
Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
by: Zhang, Baolei, et al.
Published: (2025) -
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation
by: Xu, Jie, et al.
Published: (2024) -
IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
by: Riya, Farhin Farhad, et al.
Published: (2026)