"non-iid data" Papers
19 papers found
Conference
Asynchronous Federated Clustering with Unknown Number of Clusters
Yunfan Zhang, Yiqun Zhang, Yang Lu et al.
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection
Jiahao Xu, Zikai Zhang, Rui Hu
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
Junhyeog Yun, Minui Hong, Gunhee Kim
FedSPU: Personalized Federated Learning for Resource-Constrained Devices with Stochastic Parameter Update
Ziru Niu, Hai Dong, A. K. Qin
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction
Jie Yan, Jing Liu, Zhong-Yuan Zhang
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning
Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King et al.
SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
Haoyuan Liang, Shilei Cao, Li et al.
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds
Ben Chugg, Hongjian Wang, Aaditya Ramdas
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
Sikai Bai, Shuaicheng Li, Weiming Zhuang et al.
Exploiting Label Skews in Federated Learning with Model Concatenation
Yiqun Diao, Qinbin Li, Bingsheng He
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
Hongyi Peng, Han Yu, Xiaoli Tang et al.
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels
Authors: Jichang Li, Guanbin Li, Hui Cheng et al.
Federated Causality Learning with Explainable Adaptive Optimization
Dezhi Yang, Xintong He, Jun Wang et al.
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients
Shangchao Su, Bin Li, Xiangyang Xue
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error
Yueqi Xie, Minghong Fang, Neil Gong
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan et al.
On the Asymptotic Distribution of the Minimum Empirical Risk
Jacob Westerhout, TrungTin Nguyen, Xin Guo et al.