How to get close to the median shape

In this paper, we study the problem of L1-fitting a shape to a set of n points in Rd (where d is a fixed constant), where the target is to minimize the sum of distances of the points to the shape, or alternatively the sum of squared distances. We present a general technique for computing a (1 + e)-approximation for such a problem, with running time O(n + poly(logn, 1/e)), where poly(logn, 1/e) is a polynomial of constant degree of logn and 1/e (the power of the polynomial is a function of d). This is a linear time algorithm for a fixed e > 0, and is the first subquadratic algorithm for this problem. Applications of the algorithm include best fitting either a circle, a sphere or a cylinder to a set of points when minimizing the sum of distances (or squared distances) to the respective shape.

[1]  Luis Rademacher,et al.  Matrix Approximation and Projective Clustering via Iterative Sampling , 2005 .

[2]  Sariel Har-Peled,et al.  Smaller Coresets for k-Median and k-Means Clustering , 2005, SCG.

[3]  P. Agarwal,et al.  Approximation Algorithms for Minimum-Width Annuli and Shells , 2000 .

[4]  Sariel Har-Peled,et al.  Shape fitting with outliers , 2003, SCG '03.

[5]  Alan M. Frieze,et al.  Fast monte-carlo algorithms for finding low-rank approximations , 2004, JACM.

[6]  Sariel Har-Peled,et al.  Coresets for $k$-Means and $k$-Median Clustering and their Applications , 2018, STOC 2004.

[7]  Joseph O'Rourke,et al.  Finding minimal enclosing boxes , 1985, International Journal of Computer & Information Sciences.

[8]  Jirí Matousek,et al.  On range searching with semialgebraic sets , 1992, Discret. Comput. Geom..

[9]  Hiroshi Imai,et al.  Algorithms for vertical and orthogonal L1 linear approximation of points , 1988, SCG '88.

[10]  Santosh S. Vempala,et al.  Matrix approximation and projective clustering via volume sampling , 2006, SODA '06.

[11]  Sariel Har-Peled,et al.  Efficiently approximating the minimum-volume bounding box of a point set in three dimensions , 1999, SODA '99.

[12]  Pankaj K. Agarwal,et al.  Robust Shape Fitting via Peeling and Grating Coresets , 2006, SODA '06.

[13]  Micha Sharir,et al.  Approximation and exact algorithms for minimum-width annuli and shells , 1999, SCG '99.

[14]  K. Clarkson Subgradient and sampling algorithms for l1 regression , 2005, SODA '05.

[15]  Pankaj K. Agarwal,et al.  Robust shape fitting via peeling and grating coresets , 2006, SODA 2006.

[16]  Sariel Har-Peled,et al.  On coresets for k-means and k-median clustering , 2004, STOC '04.

[17]  Timothy M. Chan Approximating the Diameter, Width, Smallest Enclosing Cylinder, and Minimum-Width Annulus , 2002, Int. J. Comput. Geom. Appl..

[18]  Timothy M. Chan Approximating the diameter, width, smallest enclosing cylinder, and minimum-width annulus , 2000, SCG '00.

[19]  Pankaj K. Agarwal,et al.  Approximating extent measures of points , 2004, JACM.

[20]  YUNHONG ZHOU,et al.  Algorithms for a Minimum Volume Enclosing Simplex in Three Dimensions , 2002, SIAM J. Comput..

[21]  Sariel Har-Peled,et al.  Separability with Outliers , 2005, ISAAC.

[22]  Jie Gao,et al.  Analysis of Incomplete Data and an Intrinsic-Dimension Helly Theorem , 2006, SODA '06.

[23]  Sariel Har-Peled,et al.  How to get close to the median shape , 2006, SCG '06.