Finding k points with minimum diameter and related problems
Journal of Algorithms
Static and dynamic algorithms for k-point clustering problems
Journal of Algorithms
When Hamming meets Euclid: the approximability of geometric TSP and MST (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Lectures on Discrete Geometry
Embeddings and non-approximability of geometric problems
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
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We prove algorithmic and hardness results for the problem of finding the largest set of a fixed diameter in the Euclidean space. In particular, we prove that if A^* is the largest subset of diameter r of n points in the Euclidean space, then for every @e0 there exists a polynomial time algorithm that outputs a set B of size at least |A^*| and of diameter at most r(2+@e). On the hardness side, roughly speaking, we show that unless P=NP for every @e0 it is not possible to guarantee the diameter r(4/3-@e) for B even if the algorithm is allowed to output a set of size (9594-@e)^-^1|A^*|.