13 citations · 15 across the 6 of their papers we have counts for
4 papers · 1 filter
InfoClus: Informative Clustering of High-dimensional Data Embeddings
Fuyin Lai, Edith Heiter, Guillaume Bied +1
Developing an understanding of high-dimensional data can be facilitated by visualizing that data using dimensionality reduction. However, the low-dimensional embeddings are often d…
Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors
Edith Heiter, Bo Kang, Ruth Seurinck +1
Conditional t-SNE (ct-SNE) is a recent extension to t-SNE that allows removal of known cluster information from the embedding, to obtain a visualization revealing structure beyond…
ExClus: Explainable Clustering on Low-dimensional Data Representations
Xander Vankwikelberge, Bo Kang, Edith Heiter +1
Dimensionality reduction and clustering techniques are frequently used to analyze complex data sets, but their results are often not easy to interpret. We consider how to support u…
Factoring out prior knowledge from low-dimensional embeddings
Edith Heiter, Jonas Fischer, Jilles Vreeken
Low-dimensional embedding techniques such as tSNE and UMAP allow visualizing high-dimensional data and therewith facilitate the discovery of interesting structure. Although they ar…