Principal component analysis (PCA) is a workhorse of modern data science...
Optimal transport provides a metric which quantifies the dissimilarity
b...
The problem of fitting distances by tree-metrics has received significan...
Many high-dimensional practical data sets have hierarchical structures
i...
Many high-dimensional and large-volume data sets of practical relevance ...
Embedding methods for mixed-curvature spaces are powerful techniques for...
Many data analysis problems can be cast as distance geometry problems in...
Hyperbolic space is a natural setting for mining and visualizing data wi...
We study the learnability of a class of compact operators known as
Schat...