On largest volume simplices and sub-determinants
Not on the map. Why?
Abstract (arXiv)
We show that the problem of finding the simplex of largest volume in the convex hull of n points in mathbbQd can be approximated with a factor of O(log d)d/2 in polynomial time. This improves upon the previously best known approximation guarantee of d(d-1)/2 by Khachiyan. On the other hand, we show that there exists a constant c>1 such that this problem cannot be approximated with a factor of cd, unless P=NP. % This improves over the 1.09 inapproximability that was previously known. Our hardness result holds even if n = O(d), in which case there exists a bar c,d-approximation algorithm that relies on recent sampling techniques, where bar c is again a constant. We show that similar results hold for the problem of finding the largest absolute value of a subdeterminant of a d× n matrix.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jun 2014.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 1; 2025: 0; 2026: 1.
6 papers.
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- 2022Scalable Sampling for Nonsymmetric Determinantal Point Processescited by 2
- 2021Computational Complexity of Normalizing Constants for the Product of Determinantal Point Processescited by 0
- 2024Experimental Design Using Interlacing Polynomialscited by 0
- 2026Contextual Slate GLM Bandits with Limited Adaptivitycited by 0
- 2026Contextual Slate GLM Bandits with Limited Adaptivity30 Jun 2026
- 2024Experimental Design Using Interlacing Polynomials15 Oct 2024
- 2022Contextual Bandits with Large Action Spaces: Made Practical12 Jul 2022
- 2022Scalable Sampling for Nonsymmetric Determinantal Point Processes20 Jan 2022
- 2021Computational Complexity of Normalizing Constants for the Product of Determinantal Point Processes28 Nov 2021
- 2021Some Inapproximability Results of MAP Inference and Exponentiated Determinantal Point Processes2 Sep 2021