@article{oai:kanazawa-u.repo.nii.ac.jp:00056520,
 author = {浅野, 哲夫 and Asano, Tetsuo and Bose, Prosenjit and Carmi, Paz and Maheshwari, Anil and Shu, Chang and Smid, Michiel H. M. and Wuhrer, Stefanie},
 journal = {CCCG 2007 - 19th Canadian Conference on Computational Geometry},
 month = {},
 note = {The distance preserving graph embedding problem is to embed vertices of a given weighted graph into points in 2-dimensional Euclidean space so that for each edge the distance between their corresponding endpoints is as close to the weight of the edge as possible. If the given graph is complete, that is, if distance constraints are given as a full matrix, then principal coordinate analysis can solve it in polynomial time. A serious disadvantage is its quadratic space requirement. In this paper we develop linear-space algorithms for this problem. A key idea is to partition a set of n objects into disjoint subsets (clusters) of size O(√n) such that the minimum inter cluster distance is maximized among all possible such partitions., CCCG2007 The 19th Canadian Conference on Computational Geometry, August 20-22, 2007, 金沢大学},
 pages = {185--188},
 title = {Linear-space algorithms for distance preserving embedding},
 year = {2007}
}