Small-dimensional linear programming and convex hulls made easy
Discrete & Computational Geometry
Helly theorems and generalized linear programming
Helly theorems and generalized linear programming
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
Helly-type theorems and geometric transversals
Handbook of discrete and computational geometry
On the hardness of approximating minimization problems
Journal of the ACM (JACM)
A Combinatorial Bound for Linear Programming and Related Problems
STACS '92 Proceedings of the 9th Annual Symposium on Theoretical Aspects of Computer Science
Improved Approximation Algorithms for Geometric Set Cover
Discrete & Computational Geometry
Clustering lines in high-dimensional space: Classification of incomplete data
ACM Transactions on Algorithms (TALG)
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Let F ∪ {U} be a collection of convex sets in Rd such that F covers U. We show that if the elements of F and U have comparable size, in the sense that each contains a ball of radius r and is contained in a ball of radius R for some fixed r and R, then for any ε 0 there exists Hε ⊂ F, whose size |Hε| is polynomial in 1/ε and independent of |F|, that covers U except for a volume of at most ε. The size of the smallest such subset depends on the geometry of the elements of F; specifically, we prove that it is O(1/ε) when F consists of axis-parallel unit squares in the plane and Õ(ε1--d/2) when F consists of unit balls in Rd (here, Õ(n) means O(n log n) for some constant), and that these bounds are, in the worst-case, tight up to the logarithmic factors. We extend these results to surface-to-surface visibility in 3 dimensions: if a collection F of disjoint unit balls occludes visibility between two balls then a subset of F of size Õ(ε--7/2) blocks visibility along all but a set of lines of measure ε. Finally, for each of the above situations we give an algorithm that takes F and U as input and outputs in time O(|F|*|Hε|) either a point in U not covered by F or a subset Hε covering U up to a measure ε, with |Hε| satisfying the above bounds.