7 citations · 7 across the 5 of their papers we have counts for
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cs.LG2026★ 7 cited
One-Shot Federated Clustering of Non-Independent Completely Distributed Data
Yiqun Zhang, Shenghong Cai, Zihua Yang +3
Federated Learning (FL) that extracts data knowledge while protecting the privacy of multiple clients has achieved remarkable results in distributed privacy-preserving IoT systems,…
cs.LG2026
Stitch the Fragments: One-Shot Hierarchical Federated Clustering
Shenghong Cai, Zihua Yang, Yang Lu +4
Federated Clustering (FC) faces a critical bottleneck in real-world scenarios, i.e., global clusters are rarely intact, often fragmenting into incomplete, multi-granular unlabeled…
cs.LG2026
Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models
Zihua Yang, Xin Liao, Yiqun Zhang +1
Qualitative data are widespread in domains such as healthcare, marketing, and bioinformatics, where clustering offers a fundamental tool for pattern discovery. A core difficulty of…