A divide-and-merge methodology for clustering
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
How fast is the k-means method?
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Matrix approximation and projective clustering via volume sampling
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
On k-Median clustering in high dimensions
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
A linear time algorithm for approximate 2-means clustering
Computational Geometry: Theory and Applications
A fast k-means implementation using coresets
Proceedings of the twenty-second annual symposium on Computational geometry
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
An investigation of computational and informational limits in Gaussian mixture clustering
ICML '06 Proceedings of the 23rd international conference on Machine learning
A divide-and-merge methodology for clustering
ACM Transactions on Database Systems (TODS)
A PTAS for k-means clustering based on weak coresets
SCG '07 Proceedings of the twenty-third annual symposium on Computational geometry
k-means++: the advantages of careful seeding
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
A linear time deterministic algorithm to find a small subset that approximates the centroid
Information Processing Letters
Clustering for metric and non-metric distance measures
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
A continuous facility location problem and its application to a clustering problem
Proceedings of the 2008 ACM symposium on Applied computing
Approximation algorithms for clustering uncertain data
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Approximation algorithms for co-clustering
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Improved smoothed analysis of the k-means method
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Approximate clustering without the approximation
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Coresets and approximate clustering for Bregman divergences
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
The Planar k-Means Problem is NP-Hard
WALCOM '09 Proceedings of the 3rd International Workshop on Algorithms and Computation
Fast approximate spectral clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
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
A linear time algorithm for approximate 2-means clustering
Computational Geometry: Theory and Applications
Random projection trees for vector quantization
IEEE Transactions on Information Theory
RACK: RApid clustering using K-means algorithm
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
Algorithms for K-means clustering problem with balancing constraint
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Small space representations for metric min-sum k-clustering and their applications
STACS'07 Proceedings of the 24th annual conference on Theoretical aspects of computer science
Clustering for metric and nonmetric distance measures
ACM Transactions on Algorithms (TALG)
Topographic mapping of large dissimilarity data sets
Neural Computation
Property testing
Property testing
Approximate polytope membership queries
Proceedings of the forty-third annual ACM symposium on Theory of computing
Smoothed Analysis of the k-Means Method
Journal of the ACM (JACM)
Center-based clustering under perturbation stability
Information Processing Letters
A voronoi diagram approach to autonomous clustering
DS'06 Proceedings of the 9th international conference on Discovery Science
Linear time algorithms for clustering problems in any dimensions
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Clustering very large dissimilarity data sets
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
Fast k-means algorithms with constant approximation
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
On autonomous k-means clustering
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Bregman clustering for separable instances
SWAT'10 Proceedings of the 12th Scandinavian conference on Algorithm Theory
Proceedings of the VLDB Endowment
Clustering 100,000 Protein Structure Decoys in Minutes
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
The planar k-means problem is NP-hard
Theoretical Computer Science
Iterative random projections for high-dimensional data clustering
Pattern Recognition Letters
The effectiveness of lloyd-type methods for the k-means problem
Journal of the ACM (JACM)
Clustering under approximation stability
Journal of the ACM (JACM)
| Hi-index | 0.06 |
We present the first linear time (1+驴)-approximation algorithm for the k-means problem for fixed k and 驴. Our algorithm runs in O(nd) time, which is linear in the size of the input. Another feature of our algorithm is its simplicity 驴 the only technique involved is random sampling.