@inproceedings{c7972bbe32e64bd99f3d3a95b7f3f179,
title = "Distance geometry in linearizable norms",
abstract = "Distance Geometry puts the concept of distance at its center. The basic problem in distance geometry could be described as drawing an edge-weighted undirected graph in RK for some given K such that the positions for adjacent vertices have distance which is equal to the corresponding edge weight. There appears to be a lack of exact methods in this field using any other norm but ℓ2. In this paper we move some first steps using the ℓ1 and ℓ∞ norms: we discuss worst-case complexity, propose mixed-integer linear programming formulations, and sketch a few heuristic ideas.",
keywords = "Distance geometry, Mathematical programming, Norms",
author = "Claudia D{\textquoteright}Ambrosio and Leo Liberti",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 3rd International Conference on Geometric Science of Information, GSI 2017 ; Conference date: 07-11-2017 Through 09-11-2017",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-68445-1\_95",
language = "English",
isbn = "9783319684444",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "830--837",
editor = "Frank Nielsen and Frederic Barbaresco and Frank Nielsen",
booktitle = "Geometric Science of Information - 3rd International Conference, GSI 2017, Proceedings",
}