Elastically-Constrained Meta-Learner for Federated Learning

no code implementations • 29 Jun 2023 • Peng Lan, Donglai Chen, Chong Xie, Keshu Chen, Jinyuan He, Juntao Zhang, Yonghong Chen, Yan Xu

One of the challenges in federated learning is non-IID data between clients, as a single model can not fit the data distribution for all clients.

Federated Learning Meta-Learning

Clustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking

no code implementations • 19 Mar 2020 • Hanlin Zhu, Xue Li, Liuyang Sun, Fei He, Zhengtuo Zhao, Lan Luan, Ngoc Mai Tran, Chong Xie

Across many areas, from neural tracking to database entity resolution, manual assessment of clusters by human experts presents a bottleneck in rapid development of scalable and specialized clustering methods.

Clustering Entity Resolution +2