The cover number of a matrix and its algorithmic applications

Given a matrix A, we study how many epsilon-cubes are required to cover the convex hull of the columns of A. We show bounds on this cover number in terms of VC dimension and the gamma_2 norm and give algorithms for enumerating elements of a cover. This leads to algorithms for computing approximate N...

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Main Authors: Lee, Troy, Alon, Noga, Shraibman, Adi
Other Authors: School of Physical and Mathematical Sciences
Format: Journal Article
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/87666
http://hdl.handle.net/10220/46788
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author Lee, Troy
Alon, Noga
Shraibman, Adi
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Lee, Troy
Alon, Noga
Shraibman, Adi
author_sort Lee, Troy
collection NTU
description Given a matrix A, we study how many epsilon-cubes are required to cover the convex hull of the columns of A. We show bounds on this cover number in terms of VC dimension and the gamma_2 norm and give algorithms for enumerating elements of a cover. This leads to algorithms for computing approximate Nash equilibria that unify and extend several previous results in the literature. Moreover, our approximation algorithms can be applied quite generally to a family of quadratic optimization problems that also includes finding the k-by-k combinatorial rectangle of a matrix. In particular, for this problem we give the first quasi-polynomial time additive approximation algorithm that works for any matrix A in [0,1]^{m x n}.
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spelling ntu-10356/876662023-02-28T19:23:47Z The cover number of a matrix and its algorithmic applications Lee, Troy Alon, Noga Shraibman, Adi School of Physical and Mathematical Sciences Approximate Nash Equilibria Approximation Algorithms DRNTU::Science::Mathematics Given a matrix A, we study how many epsilon-cubes are required to cover the convex hull of the columns of A. We show bounds on this cover number in terms of VC dimension and the gamma_2 norm and give algorithms for enumerating elements of a cover. This leads to algorithms for computing approximate Nash equilibria that unify and extend several previous results in the literature. Moreover, our approximation algorithms can be applied quite generally to a family of quadratic optimization problems that also includes finding the k-by-k combinatorial rectangle of a matrix. In particular, for this problem we give the first quasi-polynomial time additive approximation algorithm that works for any matrix A in [0,1]^{m x n}. NRF (Natl Research Foundation, S’pore) Published version 2018-12-04T05:29:15Z 2019-12-06T16:46:50Z 2018-12-04T05:29:15Z 2019-12-06T16:46:50Z 2014 Journal Article Alon, N., Lee, T., & Shraibman, A. (2014). The cover number of a matrix and its algorithmic applications. LIPIcs–Leibniz International Proceedings in Informatics, 34-47. doi:10.4230/LIPIcs.APPROX-RANDOM.2014.34 https://hdl.handle.net/10356/87666 http://hdl.handle.net/10220/46788 10.4230/LIPIcs.APPROX-RANDOM.2014.34 en LIPIcs–Leibniz International Proceedings in Informatics © 2014 The Author(s) (Leibniz International Proceedings in Informatics). Licensed under Creative Commons License CC-BY. 14 p. application/pdf
spellingShingle Approximate Nash Equilibria
Approximation Algorithms
DRNTU::Science::Mathematics
Lee, Troy
Alon, Noga
Shraibman, Adi
The cover number of a matrix and its algorithmic applications
title The cover number of a matrix and its algorithmic applications
title_full The cover number of a matrix and its algorithmic applications
title_fullStr The cover number of a matrix and its algorithmic applications
title_full_unstemmed The cover number of a matrix and its algorithmic applications
title_short The cover number of a matrix and its algorithmic applications
title_sort cover number of a matrix and its algorithmic applications
topic Approximate Nash Equilibria
Approximation Algorithms
DRNTU::Science::Mathematics
url https://hdl.handle.net/10356/87666
http://hdl.handle.net/10220/46788
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