We consider the following fitting problem: given an arbitrary set of N points in a bounded grid in dimension d, find a digital hyperplane that contains the largest possible number of points. We first observe that the problem is 3SUM-hard in the plane, so that it probably cannot be solved exactly with computational complexity better than O(N2), and it is conjectured that optimal computational complexity in dimension d is in fact O(N d). We therefore propose two approximation methods featuring linear time complexity. As the latter one is easily implemented, we present experimental results that show the runtime in practice. © 2011 Springer-Verlag.
CITATION STYLE
Aiger, D., Kenmochi, Y., Talbot, H., & Buzer, L. (2011). Efficient robust digital hyperplane fitting with bounded error. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6607 LNCS, pp. 223–234). https://doi.org/10.1007/978-3-642-19867-0_19
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