2020
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction
NeurIPS 2020poster
Nonlinear dimensionality reduction of high-dimensional data is challenging as the low-dimensional embedding will necessarily contain distortions, and it can be hard to determine which distortions are the most important to avoid. When annotation of data into known relevant classes is available, it ca…