Abstract
We study Euclidean embeddings of Euclidean metrics and present the following four results: (1) an O(log3 n√log log n) approximation for minimum bandwidth in conjunction with a semi-definite relaxation, (2) an O(log3 n) approximation in O(n log n) time using a new constraint set, (3) a lower bound of Θ(√log n) on the least possible volume distortion for Euclidean metrics, (4) a new embedding with O(√log n) distortion of point-to-subset distances.
Supported in part by NSF Career Award CCR-9875024.
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© 2001 Springer-Verlag Berlin Heidelberg
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Dunagan, J., Vempala, S. (2001). On Euclidean Embeddings and Bandwidth Minimization. In: Goemans, M., Jansen, K., Rolim, J.D.P., Trevisan, L. (eds) Approximation, Randomization, and Combinatorial Optimization: Algorithms and Techniques. RANDOM APPROX 2001 2001. Lecture Notes in Computer Science, vol 2129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44666-4_26
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DOI: https://doi.org/10.1007/3-540-44666-4_26
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