Name
Title | ||
|---|---|---|
NOISY EUCLIDEAN DISTANCE REALIZATION: ROBUST FACIAL REDUCTION AND THE PARETO FRONTIER |
Abstract | ||
|---|---|---|
We present two algorithms for large-scale noisy low-rank Euclidean distance matrix completion problems, based on semidefinite optimization. Our first method works by relating cliques in the graph of the known distances to faces of the positive semidefinite cone, yielding a combinatorial procedure that is provably robust and partly parallelizable. Our second algorithm is a first-order method for maximizing the trace a popular low-rank inducing regularizer in the formulation of the problem with a constrained misfit. Both of the methods output a point configuration that can serve as a high-quality initialization for local optimization techniques. Numerical experiments on large-scale sensor localization problems illustrate the two approaches. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1137/15M103710X | SIAM JOURNAL ON OPTIMIZATION |
Keywords | DocType | Volume |
Euclidean distance matrices,sensor network localization,convex optimization,facial reduction,Frank Wolfe algorithm,semidefinite programming | Journal | 27 |
Issue | ISSN | Citations |
4 | 1052-6234 | 3 |
PageRank | References | Authors |
0.40 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dmitriy Drusvyatskiy | 1 | 166 | 17.25 |
| Nathan Krislock | 2 | 107 | 6.22 |
| yuenlam voronin | 3 | 5 | 0.82 |
| Henry Wolkowicz | 4 | 1444 | 260.72 |