181 citations · 243 across the 7 of their papers we have counts for
4 papers · 1 filter
UMATO: Bridging Local and Global Structures for Reliable Visual Analytics with Dimensionality Reduction
Hyeon Jeon, Kwon Ko, Soohyun Lee +5
Due to the intrinsic complexity of high-dimensional (HD) data, dimensionality reduction (DR) techniques cannot preserve all the structural characteristics of the original data. The…
ZADU: A Python Library for Evaluating the Reliability of Dimensionality Reduction Embeddings
Hyeon Jeon, Aeri Cho, Jinhwa Jang +5
Dimensionality reduction (DR) techniques inherently distort the original structure of input high-dimensional data, producing imperfect low-dimensional embeddings. Diverse distortio…
Uniform Manifold Approximation with Two-phase Optimization
Hyeon Jeon, Hyung-Kwon Ko, Soohyun Lee +2
We introduce Uniform Manifold Approximation with Two-phase Optimization (UMATO), a dimensionality reduction (DR) technique that improves UMAP to capture the global structure of hig…
Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections
Hyeon Jeon, Hyung-Kwon Ko, Jaemin Jo +2
We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster reliability of multidimensional projection (MDP), specifically how well the inter-cluster str…