The field of explorative data analysis provides methods to investigate large, potentially high-dimensional, data sets. Such exploration is best done visually, to engage the human in the loop with all pattern recognition built into our visual cortex. In my talk, I will give a brief introduction to dimensionality reduction for this purpose, especially about the t-SNE method. I will then show how embedding into non-Euclidean spaces can provide embeddings that help with visual inspection and how to compute such embeddings quickly.
De Martin Skrodzki
De Claire David
De Martin Traizet
De Alexander Bobenko
De Romain Dujardin
De Romain Dujardin
De Romain Dujardin
De Dalia Terhesiu
