Localization from structured distance matrices via low-rank matrix recovery
S Lichtenberg, A Tasissa - IEEE Transactions on Information …, 2024 - ieeexplore.ieee.org
We study the problem of determining the configuration of n points by using their distances to
m nodes, referred to as anchor nodes. One sampling scheme is Nyström sampling, which …
m nodes, referred to as anchor nodes. One sampling scheme is Nyström sampling, which …
Riemannian optimization for non-convex Euclidean distance geometry with global recovery guarantees
The problem of determining the configuration of points from partial distance information,
known as the Euclidean Distance Geometry (EDG) problem, is fundamental to many tasks in …
known as the Euclidean Distance Geometry (EDG) problem, is fundamental to many tasks in …
Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
The problem of finding suitable point embedding or geometric configurations given only
Euclidean distance information of point pairs arises both as a core task and as a sub …
Euclidean distance information of point pairs arises both as a core task and as a sub …
One-step Spectral Estimation for Euclidean Distance Matrix Approximation
Y Li, X Sun - 2024 Asia Pacific Signal and Information …, 2024 - ieeexplore.ieee.org
This paper proposes and analyzes a new spectral estimator for Euclidean Distance Matrix
Completion (EDMC) problem under Bernoulli sample model. This new estimator can be …
Completion (EDMC) problem under Bernoulli sample model. This new estimator can be …