Poster "non-iid data" Papers
12 papers found
Conference
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
Junhyeog Yun, Minui Hong, Gunhee Kim
ICCV 2025arXiv:2508.06301
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
NEURIPS 2025
2
citations
OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction
Jie Yan, Jing Liu, Zhong-Yuan Zhang
NEURIPS 2025arXiv:2505.13071
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
ICLR 2025arXiv:2503.08085
3
citations
Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning
Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King et al.
ICCV 2025arXiv:2508.01251
SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
Haoyuan Liang, Shilei Cao, Li et al.
NEURIPS 2025
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds
Ben Chugg, Hongjian Wang, Aaditya Ramdas
ICML 2024arXiv:2302.03421
32
citations
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
Hongyi Peng, Han Yu, Xiaoli Tang et al.
ICML 2024arXiv:2405.15458
9
citations
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients
Shangchao Su, Bin Li, Xiangyang Xue
ECCV 2024arXiv:2311.11227
21
citations
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error
Yueqi Xie, Minghong Fang, Neil Gong
ICML 2024
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan et al.
ICML 2024arXiv:2405.06822
15
citations
On the Asymptotic Distribution of the Minimum Empirical Risk
Jacob Westerhout, TrungTin Nguyen, Xin Guo et al.
ICML 2024