Distance Shrinkage and Euclidean Embedding via Regularized Kernel Estimation

17 Sep 2014 Luwan Zhang Grace Wahba Ming Yuan

Although recovering an 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 upon the so-called regularized kernel estimate... (read more)

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