NeurIPS "data heterogeneity" Papers

Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning

Dipam Goswami, Simone Magistri, Kai Wang et al.

DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning

Yueyang Yuan, Wenke Huang, Guancheng Wan et al.

Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients

Shiyuan Zuo, Xingrun Yan, Rongfei Fan et al.

Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable

Bicheng Ying, Zhe Li, Haibo Yang

FedEL: Federated Elastic Learning for Heterogeneous Devices

Letian Zhang, Bo Chen, Jieming Bian et al.

FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning

Zhiqin Yang, Yonggang Zhang, Chenxin Li et al.

FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling

Hong Huang, Jinhai Yang, Yuan Chen et al.

Revisiting Consensus Error: A Fine-grained Analysis of Local SGD under Second-order Data Heterogeneity

Kumar Kshitij Patel, Ali Zindari, Sebastian Stich et al.

Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation

Xinghao Wu, Xuefeng Liu, Jianwei Niu et al.

Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training