2023
Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
NeurIPS 2023poster
We extend metric learning by studying the Riemannian manifold structure of the underlying data space induced by similarity measures between data points. The key quantity of interest here is the Riemannian metric, which characterizes the Riemannian geometry and defines straight lines and derivatives…