Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning
Fuente:
arXiv
Guardado en:
| Autores principales: | Liu, Yuchen, Chen, Chen, Lyu, Lingjuan, Jin, Yaochu, Chen, Gang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
por: Zhuang, Weiming, et al.
Publicado: (2023)
por: Zhuang, Weiming, et al.
Publicado: (2023)
BOBA: Byzantine-Robust Federated Learning with Label Skewness
por: Bao, Wenxuan, et al.
Publicado: (2022)
por: Bao, Wenxuan, et al.
Publicado: (2022)
FedMef: Towards Memory-efficient Federated Dynamic Pruning
por: Huang, Hong, et al.
Publicado: (2024)
por: Huang, Hong, et al.
Publicado: (2024)
Closer to Reality: Practical Semi-Supervised Federated Learning for Foundation Model Adaptation
por: Sun, Guangyu, et al.
Publicado: (2025)
por: Sun, Guangyu, et al.
Publicado: (2025)
OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models
por: Yan, Yuping, et al.
Publicado: (2025)
por: Yan, Yuping, et al.
Publicado: (2025)
Exploiting Label Skewness for Spiking Neural Networks in Federated Learning
por: Yu, Di, et al.
Publicado: (2024)
por: Yu, Di, et al.
Publicado: (2024)
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective
por: Zhang, Zhongjian, et al.
Publicado: (2025)
por: Zhang, Zhongjian, et al.
Publicado: (2025)
Byzantine-Robust Decentralized Federated Learning
por: Fang, Minghong, et al.
Publicado: (2024)
por: Fang, Minghong, et al.
Publicado: (2024)
SpectralKrum: A Spectral-Geometric Defense Against Byzantine Attacks in Federated Learning
por: Tripathi, Aditya, et al.
Publicado: (2025)
por: Tripathi, Aditya, et al.
Publicado: (2025)
FedWon: Triumphing Multi-domain Federated Learning Without Normalization
por: Zhuang, Weiming, et al.
Publicado: (2023)
por: Zhuang, Weiming, et al.
Publicado: (2023)
Understanding the Role of Layer Normalization in Label-Skewed Federated Learning
por: Zhang, Guojun, et al.
Publicado: (2023)
por: Zhang, Guojun, et al.
Publicado: (2023)
FEDEXCHANGE: Bridging the Domain Gap in Federated Object Detection for Free
por: Yuan, Haolin, et al.
Publicado: (2025)
por: Yuan, Haolin, et al.
Publicado: (2025)
Sybil-based Virtual Data Poisoning Attacks in Federated Learning
por: Zhu, Changxun, et al.
Publicado: (2025)
por: Zhu, Changxun, et al.
Publicado: (2025)
Asynchronous Byzantine Federated Learning
por: Cox, Bart, et al.
Publicado: (2024)
por: Cox, Bart, et al.
Publicado: (2024)
Trade-off in Estimating the Number of Byzantine Clients in Federated Learning
por: Chen, Ziyi, et al.
Publicado: (2025)
por: Chen, Ziyi, et al.
Publicado: (2025)
Nesterov-Accelerated Robust Federated Learning Over Byzantine Adversaries
por: Xu, Lihan, et al.
Publicado: (2025)
por: Xu, Lihan, et al.
Publicado: (2025)
Robust Decentralized Multi-armed Bandits: From Corruption-Resilience to Byzantine-Resilience
por: Hu, Zicheng, et al.
Publicado: (2025)
por: Hu, Zicheng, et al.
Publicado: (2025)
Can Textual Gradient Work in Federated Learning?
por: Chen, Minghui, et al.
Publicado: (2025)
por: Chen, Minghui, et al.
Publicado: (2025)
Integration of Large Language Models and Federated Learning
por: Chen, Chaochao, et al.
Publicado: (2023)
por: Chen, Chaochao, et al.
Publicado: (2023)
Enhancing the Effectiveness and Durability of Backdoor Attacks in Federated Learning through Maximizing Task Distinction
por: Wang, Zhaoxin, et al.
Publicado: (2025)
por: Wang, Zhaoxin, et al.
Publicado: (2025)
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
por: Zhong, Zhengyi, et al.
Publicado: (2025)
por: Zhong, Zhengyi, et al.
Publicado: (2025)
Reducing Communication for Split Learning by Randomized Top-k Sparsification
por: Zheng, Fei, et al.
Publicado: (2023)
por: Zheng, Fei, et al.
Publicado: (2023)
Federated Learning over a Wireless Network: Distributed User Selection through Random Access
por: Sun, Chen, et al.
Publicado: (2023)
por: Sun, Chen, et al.
Publicado: (2023)
IRIS: Implicit Reward-Guided Internal Sifting for Mitigating Multimodal Hallucination
por: Li, Yuanshuai, et al.
Publicado: (2026)
por: Li, Yuanshuai, et al.
Publicado: (2026)
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity
por: Chen, Yuhang, et al.
Publicado: (2024)
por: Chen, Yuhang, et al.
Publicado: (2024)
Communication-Efficient Federated Learning by Exploiting Spatio-Temporal Correlations of Gradients
por: Zheng, Shenlong, et al.
Publicado: (2026)
por: Zheng, Shenlong, et al.
Publicado: (2026)
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
por: Luo, Xinjian, et al.
Publicado: (2020)
por: Luo, Xinjian, et al.
Publicado: (2020)
Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning
por: Chen, Mengmeng, et al.
Publicado: (2025)
por: Chen, Mengmeng, et al.
Publicado: (2025)
Heterogeneous Federated Learning with Convolutional and Spiking Neural Networks
por: Yu, Yingchao, et al.
Publicado: (2024)
por: Yu, Yingchao, et al.
Publicado: (2024)
Gradient Purification: Defense Against Poisoning Attack in Decentralized Federated Learning
por: Li, Bin, et al.
Publicado: (2025)
por: Li, Bin, et al.
Publicado: (2025)
Poisoning with A Pill: Circumventing Detection in Federated Learning
por: Guo, Hanxi, et al.
Publicado: (2024)
por: Guo, Hanxi, et al.
Publicado: (2024)
Replay-Free Continual Low-Rank Adaptation with Dynamic Memory
por: Chen, Huancheng, et al.
Publicado: (2024)
por: Chen, Huancheng, et al.
Publicado: (2024)
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
por: Yi, Kai, et al.
Publicado: (2024)
por: Yi, Kai, et al.
Publicado: (2024)
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis
por: Wang, Jiaqi, et al.
Publicado: (2024)
por: Wang, Jiaqi, et al.
Publicado: (2024)
TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data
por: Yan, Yuping, et al.
Publicado: (2025)
por: Yan, Yuping, et al.
Publicado: (2025)
Local Data Quantity-Aware Weighted Averaging for Federated Learning with Dishonest Clients
por: Wu, Leming, et al.
Publicado: (2025)
por: Wu, Leming, et al.
Publicado: (2025)
AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning
por: Tang, Zehui, et al.
Publicado: (2026)
por: Tang, Zehui, et al.
Publicado: (2026)
Federated Incomplete Multi-View Clustering with Heterogeneous Graph Neural Networks
por: Yan, Xueming, et al.
Publicado: (2024)
por: Yan, Xueming, et al.
Publicado: (2024)
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
por: Zheng, Xiaosen, et al.
Publicado: (2024)
por: Zheng, Xiaosen, et al.
Publicado: (2024)
Byzantine Resilient Federated Multi-Task Representation Learning
por: Le, Tuan, et al.
Publicado: (2025)
por: Le, Tuan, et al.
Publicado: (2025)
Ejemplares similares
-
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
por: Zhuang, Weiming, et al.
Publicado: (2023) -
BOBA: Byzantine-Robust Federated Learning with Label Skewness
por: Bao, Wenxuan, et al.
Publicado: (2022) -
FedMef: Towards Memory-efficient Federated Dynamic Pruning
por: Huang, Hong, et al.
Publicado: (2024) -
Closer to Reality: Practical Semi-Supervised Federated Learning for Foundation Model Adaptation
por: Sun, Guangyu, et al.
Publicado: (2025) -
OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models
por: Yan, Yuping, et al.
Publicado: (2025)