SCG '94 Proceedings of the tenth annual symposium on Computational geometry
Approximation schemes for clustering problems
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Clustering Large Graphs via the Singular Value Decomposition
Machine Learning
A local search approximation algorithm for k-means clustering
Computational Geometry: Theory and Applications - Special issue on the 18th annual symposium on computational geometrySoCG2002
A Simple Linear Time (1+ ") -Approximation Algorithm for k-Means Clustering in Any Dimensions
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
How fast is the k-means method?
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
How slow is the k-means method?
Proceedings of the twenty-second annual symposium on Computational geometry
Worst-case and Smoothed Analysis of the ICP Algorithm, with an Application to the k-means Method
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
The Effectiveness of Lloyd-Type Methods for the k-Means Problem
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
k-means++: the advantages of careful seeding
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
On clustering to minimize the sum of radii
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
SFCS '80 Proceedings of the 21st Annual Symposium on Foundations of Computer Science
The directed planar reachability problem
FSTTCS '05 Proceedings of the 25th international conference on Foundations of Software Technology and Theoretical Computer Science
Adaptive Sampling for k-Means Clustering
APPROX '09 / RANDOM '09 Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
Viterbi training for PCFGs: hardness results and competitiveness of uniform initialization
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Smoothed Analysis of the k-Means Method
Journal of the ACM (JACM)
A highly parallel implementation of k-means for multithreaded architecture
Proceedings of the 19th High Performance Computing Symposia
Data reduction for weighted and outlier-resistant clustering
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Automation and Remote Control
The MADlib analytics library: or MAD skills, the SQL
Proceedings of the VLDB Endowment
The impact of ICT development on the global digital divide
Electronic Commerce Research and Applications
Size Constrained Distance Clustering: Separation Properties and Some Complexity Results
Fundamenta Informaticae - From Physics to Computer Science: to Gianpiero Cattaneo for his 70th birthday
Clustering under approximation stability
Journal of the ACM (JACM)
Optimising sum-of-squares measures for clustering multisets defined over a metric space
Discrete Applied Mathematics
Theoretical Computer Science
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In the k-means problem, we are given a finite set S of points in $\Re^m$, and integer k ≥ 1, and we want to find k points (centers) so as to minimize the sum of the square of the Euclidean distance of each point in S to its nearest center. We show that this well-known problem is NP-hard even for instances in the plane, answering an open question posed by Dasgupta [6].