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Let S denote a set of n points in d-dimensional space, Rd, and let dist(p, g) denote the distance between two points in any Minkowski metric. For any real E > 0 and q E Rd, a point p E S is a (1 +… (More)

- Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, Angela Y. Wu
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2002

ÐIn k-means clustering, we are given a set of n data points in d-dimensional space R and an integer k and the problem is to determine a set of k points in R, called centers, so as to minimize the… (More)

- Sunil Arya, David M. Mount, Nathan S. Netanyahu, Ruth Silverman, Angela Y. Wu
- J. ACM
- 1998

Consider a set of <italic>S</italic> of <italic>n</italic> data points in real <italic>d</italic>-dimensional space, R<supscrpt>d</supscrpt>, where distances are measured using any Minkowski metric.… (More)

- Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, Angela Y. Wu
- Symposium on Computational Geometry
- 2002

In k-means clustering we are given a set of n data points in d-dimensional space Rd and an integer k, and the problem is to determine a set of k points in ÓC;d, called centers, to minimize the mean… (More)

- David M. Mount, Ruth Silverman, Angela Y. Wu
- Computer Vision and Image Understanding
- 1996

Given two simple polygons P and Q in the plane and a translation vector t 2 R 2 , the area-of-overlap function of P and Q is the function Ar(t) = Area(P \ (t + Q)), where t + Q denotes Q translated… (More)

- David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, Angela Y. Wu
- Algorithmica
- 2012

The linear least trimmed squares (LTS) estimator is a statistical technique for fitting a linear model to a set of points. Given a set of n points in ℝ d and given an integer trimming parameter h≤n,… (More)

- David M. Mount, Nathan S. Netanyahu, Ruth Silverman, Angela Y. Wu
- Comput. Geom.
- 2000

The nearest neighbor problem is that of preprocessing a set P of n data points in Rd so that, given any query point q, the closest point in P to q can be determined efficiently. In the chromatic… (More)

Clustering is an important problem, with applications in areas such as data mining and knowledge discovery [6], data compression and vector quantiation [S], and pattern recognition and pattern… (More)

- Kanungoy, Meǵıas David, +6 authors Angela Y. Wu
- 2000

K-means clustering is a very popular clustering technique, which is used in numerous applications. Given a set of n data points in R d and an integer k, the problem is to determine a set of k points… (More)

- Shyuan Wang, Angela Y. Wu, Azriel Rosenfeld
- IEEE Transactions on Pattern Analysis and Machine…
- 1981

Several types of gray-weighted ``medial axes'' have been defined. This paper shows that one of them, the min-max medial axis, can be used to reconstruct good approximations to the original image… (More)