Discrete & Computational Geometry

, Volume 40, Issue 4, pp 537–560

# Analysis of Incomplete Data and an Intrinsic-Dimension Helly Theorem

Article

## Abstract

The analysis of incomplete data is a long-standing challenge in practical statistics. When, as is typical, data objects are represented by points in ℝ d , incomplete data objects correspond to affine subspaces (lines or Δ-flats). With this motivation we study the problem of finding the minimum intersection radius r(ℒ) of a set of lines or Δ-flats ℒ: the least r such that there is a ball of radius r intersecting every flat in ℒ. Known algorithms for finding the minimum enclosing ball for a point set (or clustering by several balls) do not easily extend to higher-dimensional flats, primarily because “distances” between flats do not satisfy the triangle inequality. In this paper we show how to restore geometry (i.e., a substitute for the triangle inequality) to the problem, through a new analog of Helly’s theorem. This “intrinsic-dimension” Helly theorem states: for any family ℒ of Δ-dimensional convex sets in a Hilbert space, there exist Δ+2 sets ℒ′⊆ℒ such that r(ℒ)≤2r(ℒ′). Based upon this we present an algorithm that computes a (1+ε)-core set ℒ′⊆ℒ, |ℒ′|=O(Δ 4/ε), such that the ball centered at a point c with radius (1+ε)r(ℒ′) intersects every element of ℒ. The running time of the algorithm is O(n Δ+1 dpoly (Δ/ε)). For the case of lines or line segments (Δ=1), the (expected) running time of the algorithm can be improved to O(ndpoly (1/ε)). We note that the size of the core set depends only on the dimension of the input objects and is independent of the input size n and the dimension d of the ambient space.

### Keywords

Clustering k-center Core set Incomplete data Helly theorem Approximation Inference

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## Authors and Affiliations

• Jie Gao
• 1
• Michael Langberg
• 2
• Leonard J. Schulman
• 3
1. 1.Department of Computer ScienceStony Brook UniversityStony BrookUSA
2. 2.Computer Science DivisionThe Open University of IsraelRaananaIsrael
3. 3.Department of Computer ScienceCalifornia Institute of TechnologyPasadenaUSA