activity
20192025
most citedWeighted Clustering Ensemble: A Review

62 citations · 80 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Shape-Informed Clustering of Multi-Dimensional Functional Data via Deep Functional Autoencoders

Samuel Singh, Shirley Coyle, Mimi Zhang

We introduce FAEclust, a novel functional autoencoder framework for cluster analysis of multi-dimensional functional data, data that are random realizations of vector-valued random…

stat.AP2025

Ireland Topsoil Contamination Analysis: A Clustering Approach

Mimi Zhang

This study investigates topsoil contamination in Ireland using geochemical data from the Tellus Programme, analyzing 4,278 soil samples across 17,983 square kilometer. The research…

stat.ME2024★ 2 cited

Co-Clustering Multi-View Data Using the Latent Block Model

Joshua Tobin, Michaela Black, James Ng +11

The Latent Block Model (LBM) is a prominent model-based co-clustering method, returning parametric representations of each block cluster and allowing the use of well-grounded model…

cs.LG2021★ 16 cited

Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing

Mimi Zhang, Andrew Parnell, Dermot Brabazon +1

Bayesian optimization (BO) is an approach to globally optimizing black-box objective functions that are expensive to evaluate. BO-powered experimental design has found wide applica…

cs.CV2019★ 62 cited

Weighted Clustering Ensemble: A Review

Mimi Zhang

Clustering ensemble, or consensus clustering, has emerged as a powerful tool for improving both the robustness and the stability of results from individual clustering methods. Weig…