16 citations · 25 across the 10 of their papers we have counts for
3 papers · 1 filter
Classes are not Clusters: Improving Label-based Evaluation of Dimensionality Reduction
Hyeon Jeon, Yun-Hsin Kuo, Michaël Aupetit +2
A common way to evaluate the reliability of dimensionality reduction (DR) embeddings is to quantify how well labeled classes form compact, mutually separated clusters in the embedd…
Feature Learning for Nonlinear Dimensionality Reduction toward Maximal Extraction of Hidden Patterns
Takanori Fujiwara, Yun-Hsin Kuo, Anders Ynnerman +1
Dimensionality reduction (DR) plays a vital role in the visual analysis of high-dimensional data. One main aim of DR is to reveal hidden patterns that lie on intrinsic low-dimensio…
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data
Yun-Hsin Kuo, Takanori Fujiwara, Charles C. -K. Chou +2
Analyzing air pollution data is challenging as there are various analysis focuses from different aspects: feature (what), space (where), and time (when). As in most geospatial anal…