Data structures and algorithms 3: multi-dimensional searching and computational geometry
Data structures and algorithms 3: multi-dimensional searching and computational geometry
Computational geometry: an introduction
Computational geometry: an introduction
An optimal algorithm for finding minimal enclosing triangles
Journal of Algorithms
Clustering algorithms based on minimum and maximum spanning trees
SCG '88 Proceedings of the fourth annual symposium on Computational geometry
Finding k points with minimum diameter and related problems
Journal of Algorithms
Applications of parametric searching in geometric optimization
SODA selected papers from the third annual ACM-SIAM symposium on Discrete algorithms
Static and dynamic algorithms for k-point clustering problems
Journal of Algorithms
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Enclosing k points in the smallest axis parallel rectangle
Information Processing Letters
Clustering Algorithms
Static and Dynamic Algorithms for k-Point Clustering Problems
WADS '93 Proceedings of the Third Workshop on Algorithms and Data Structures
Smallest k-point enclosing rectangle and square of arbitrary orientation
Information Processing Letters
Covering points by disjoint boxes with outliers
Computational Geometry: Theory and Applications
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Let P be a set of n points in the plane. Here we present an efficient algorithm to compute the smallest square containing at least k points of P for large values of k. The worst case time complexity of the algorithm is O(n + (n - k) log2(n - k)) using O(n) space which is the best known bound for worst case time complexity.