Distance Shrinkage and Euclidean Embedding via Regularized Kernel Estimation
Distance Shrinkage and Euclidean Embedding via Regularized Kernel Estimation
Summary Although recovering a Euclidean distance matrix from noisy observations is a common problem in practice, how well this could be done remains largely unknown. To fill in this void, we study a simple distance matrix estimate based on the so-called regularized kernel estimate. We show that such an estimate …