3 papers
cs.LG2026
Scalable Varied-Density Clustering via Graph Propagation
Ninh Pham, Yingtao Zheng, Hugo Phibbs
We propose a novel perspective on varied-density clustering for high-dimensional data by framing it as a label propagation process in neighborhood graphs that adapt to local densit…
cs.LG2026
Towards Robust and Scalable Density-based Clustering via Graph Propagation
Yingtao Zheng, Hugo Phibbs, Ninh Pham
We present \textit{CluProp}, a novel framework that reimagines varied-density clustering in high-dimensional spaces as a label propagation process over neighborhood graphs. Our app…
cs.LG2026
CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness
Ying Zheng, Yangfan Jiang, Kian-Lee Tan
Causal fairness in databases is crucial to preventing biased and inaccurate outcomes in downstream tasks. While most prior work assumes a known causal model, recent efforts relax t…