2 papers
cs.LG2026
When One Point Is Not Enough: Addressing Ambiguous Instances in Dimensionality Reduction by Splitting
Diede P. M. van der Hoorn, Alessio Arleo, Fernando V. Paulovich
Dimensionality Reduction (DR) methods are widely used to visualize high-dimensional data. One key task in DR-based analysis is discovering neighborhoods, which relies on analyzing…
cs.LG2025
Why Can't I See My Clusters? A Precision-Recall Approach to Dimensionality Reduction Validation
Diede P. M. van der Hoorn, Alessio Arleo, Fernando V. Paulovich
Dimensionality Reduction (DR) is widely used for visualizing high-dimensional data, often with the goal of revealing expected cluster structure. However, such a structure may not a…