K-means clustering (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "K-means clustering" in English language version.

refsWebsite

Global rank English rank

29doi.org

2^nd place

13semanticscholar.org

11^th place

8^th place

7arxiv.org

69^th place

59^th place

4worldcat.org

5^th place

4harvard.edu

18^th place

17^th place

4nih.gov

4^th place

3ams.org

451^st place

277^th place

2zbmath.org

1,923^rd place

1,068^th place

2psu.edu

207^th place

136^th place

2jstor.org

26^th place

20^th place

2web.archive.org

1^st place

2researchgate.net

120^th place

125^th place

2uta.edu

low place

6,493^rd place

2acm.org

1,185^th place

840^th place

2ucsd.edu

1,933^rd place

1,342^nd place

2stanford.edu

179^th place

183^rd place

1projecteuclid.org

3,707^th place

2,409^th place

1toronto.edu

low place

8,821^st place

1cam.ac.uk

670^th place

480^th place

1mit.edu

415^th place

327^th place

1iitk.ac.in

6,454^th place

4,437^th place

1umd.edu

1,747^th place

1,277^th place

1mpg.de

1,624^th place

1,592^nd place

1uef.fi

low place

1nips.cc

low place

7,050^th place

1mlr.press

low place

1informs.org

low place

9,066^th place

1le.ac.uk

5,357^th place

3,654^th place

1icml.cc

low place

1cmu.edu

1,564^th place

1,028^th place

1aclweb.org

low place

6,793^rd place

1nrbook.com

low place

1technion.ac.il

low place

1gatech.edu

4,448^th place

2,923^rd place

1huji.ac.il

3,903^rd place

3,632^nd place

aclweb.org

Lin, Dekang; Wu, Xiaoyun (2009). Phrase clustering for discriminative learning (PDF). Annual Meeting of the ACL and IJCNLP. pp. 1030–1038.

acm.org

portal.acm.org

Pelleg, Dan; Moore, Andrew (1999). "Accelerating exact k -means algorithms with geometric reasoning". Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. San Diego, California, United States: ACM Press. pp. 277–281. doi:10.1145/312129.312248. ISBN 9781581131437. S2CID 13907420.

dl.acm.org

Sculley, David (2010). "Web-scale k-means clustering". Proceedings of the 19th international conference on World Wide Web. ACM. pp. 1177–1178. Retrieved 2016-12-21.

ams.org

mathscinet.ams.org

MacQueen, J. B. (1967). Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. Vol. 1. University of California Press. pp. 281–297. MR 0214227. Zbl 0214.46201. Retrieved 2009-04-07.
Steinhaus, Hugo (1957). "Sur la division des corps matériels en parties". Bull. Acad. Polon. Sci. (in French). 4 (12): 801–804. MR 0090073. Zbl 0079.16403.
MacKay, David (2003). "Chapter 20. An Example Inference Task: Clustering" (PDF). Information Theory, Inference and Learning Algorithms. Cambridge University Press. pp. 284–292. ISBN 978-0-521-64298-9. MR 2012999.

arxiv.org

Celebi, M. E.; Kingravi, H. A.; Vela, P. A. (2013). "A comparative study of efficient initialization methods for the k-means clustering algorithm". Expert Systems with Applications. 40 (1): 200–210. arXiv:1209.1960. doi:10.1016/j.eswa.2012.07.021. S2CID 6954668.
Arthur, David; Manthey, B.; Roeglin, H. (2009). "k-means has polynomial smoothed complexity". Proceedings of the 50th Symposium on Foundations of Computer Science (FOCS). arXiv:0904.1113.
Dasgupta, S.; Freund, Y. (July 2009). "Random Projection Trees for Vector Quantization". IEEE Transactions on Information Theory. 55 (7): 3229–42. arXiv:0805.1390. doi:10.1109/TIT.2009.2021326. S2CID 666114.
Amorim, R. C.; Hennig, C. (2015). "Recovering the number of clusters in data sets with noise features using feature rescaling factors". Information Sciences. 324: 126–145. arXiv:1602.06989. doi:10.1016/j.ins.2015.06.039. S2CID 315803.
Piccialli, Veronica; Sudoso, Antonio M.; Wiegele, Angelika (2022-03-28). "SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering". INFORMS Journal on Computing. 34 (4): 2144–2162. arXiv:2104.11542. doi:10.1287/ijoc.2022.1166. ISSN 1091-9856. S2CID 233388043.
Gribel, Daniel; Vidal, Thibaut (2019). "HG-means: A scalable hybrid metaheuristic for minimum sum-of-squares clustering". Pattern Recognition. 88: 569–583. arXiv:1804.09813. doi:10.1016/j.patcog.2018.12.022. S2CID 13746584.
Cohen, Michael B.; Elder, Sam; Musco, Cameron; Musco, Christopher; Persu, Madalina (2014). "Dimensionality reduction for k-means clustering and low rank approximation (Appendix B)". arXiv:1410.6801 [cs.DS].

cam.ac.uk

inference.phy.cam.ac.uk

MacKay, David (2003). "Chapter 20. An Example Inference Task: Clustering" (PDF). Information Theory, Inference and Learning Algorithms. Cambridge University Press. pp. 284–292. ISBN 978-0-521-64298-9. MR 2012999.

cmu.edu

cs.cmu.edu

Csurka, Gabriella; Dance, Christopher C.; Fan, Lixin; Willamowski, Jutta; Bray, Cédric (2004). Visual categorization with bags of keypoints (PDF). ECCV Workshop on Statistical Learning in Computer Vision.

doi.org

Kriegel, Hans-Peter; Schubert, Erich; Zimek, Arthur (2016). "The (black) art of runtime evaluation: Are we comparing algorithms or implementations?". Knowledge and Information Systems. 52 (2): 341–378. doi:10.1007/s10115-016-1004-2. ISSN 0219-1377. S2CID 40772241.
Lloyd, Stuart P. (1957). "Least square quantization in PCM". Bell Telephone Laboratories Paper. Published in journal much later: Lloyd, Stuart P. (1982). "Least squares quantization in PCM" (PDF). IEEE Transactions on Information Theory. 28 (2): 129–137. CiteSeerX 10.1.1.131.1338. doi:10.1109/TIT.1982.1056489. S2CID 10833328. Retrieved 2009-04-15.
Pelleg, Dan; Moore, Andrew (1999). "Accelerating exact k -means algorithms with geometric reasoning". Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. San Diego, California, United States: ACM Press. pp. 277–281. doi:10.1145/312129.312248. ISBN 9781581131437. S2CID 13907420.
Celebi, M. E.; Kingravi, H. A.; Vela, P. A. (2013). "A comparative study of efficient initialization methods for the k-means clustering algorithm". Expert Systems with Applications. 40 (1): 200–210. arXiv:1209.1960. doi:10.1016/j.eswa.2012.07.021. S2CID 6954668.
Vattani, A. (2011). "k-means requires exponentially many iterations even in the plane" (PDF). Discrete and Computational Geometry. 45 (4): 596–616. doi:10.1007/s00454-011-9340-1. S2CID 42683406.
Aloise, D.; Deshpande, A.; Hansen, P.; Popat, P. (2009). "NP-hardness of Euclidean sum-of-squares clustering". Machine Learning. 75 (2): 245–249. doi:10.1007/s10994-009-5103-0.
Dasgupta, S.; Freund, Y. (July 2009). "Random Projection Trees for Vector Quantization". IEEE Transactions on Information Theory. 55 (7): 3229–42. arXiv:0805.1390. doi:10.1109/TIT.2009.2021326. S2CID 666114.
Mahajan, Meena; Nimbhorkar, Prajakta; Varadarajan, Kasturi (2009). "The Planar k-Means Problem is NP-Hard". WALCOM: Algorithms and Computation. Lecture Notes in Computer Science. Vol. 5431. pp. 274–285. doi:10.1007/978-3-642-00202-1_24. ISBN 978-3-642-00201-4.
Inaba, M.; Katoh, N.; Imai, H. (1994). Applications of weighted Voronoi diagrams and randomization to variance-based k-clustering. Proceedings of 10th ACM Symposium on Computational Geometry. pp. 332–9. doi:10.1145/177424.178042.
Arthur, David; Vassilvitskii, Sergei (2006-01-01). "How slow is the k -means method?". Proceedings of the twenty-second annual symposium on Computational geometry. SCG '06. ACM. pp. 144–153. doi:10.1145/1137856.1137880. ISBN 978-1595933409. S2CID 3084311.
Phillips, Steven J. (2002). "Acceleration of K-Means and Related Clustering Algorithms". In Mount, David M.; Stein, Clifford (eds.). Acceleration of k-Means and Related Clustering Algorithms. Lecture Notes in Computer Science. Vol. 2409. Springer. pp. 166–177. doi:10.1007/3-540-45643-0_13. ISBN 978-3-540-43977-6.
Hamerly, Greg (2010). "Making k-means even faster". Proceedings of the 2010 SIAM International Conference on Data Mining. pp. 130–140. doi:10.1137/1.9781611972801.12. ISBN 978-0-89871-703-7.
Hamerly, Greg; Drake, Jonathan (2015). "Accelerating Lloyd's Algorithm for k-Means Clustering". Partitional Clustering Algorithms. pp. 41–78. doi:10.1007/978-3-319-09259-1_2. ISBN 978-3-319-09258-4.
Abiodun M. Ikotun, Absalom E. Ezugwu, Laith Abualigah, Belal Abuhaija, Jia Heming, K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data, Information Sciences, Volume 622, 2023, Pages 178–210, ISSN 0020-0255, https://doi.org/10.1016/j.ins.2022.11.139.
Hubert, L., & Arabie, P. (1985). Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1), 193-218. https://doi.org/10.1007/BF01908075
Kanungo, Tapas; Mount, David M.; Netanyahu, Nathan S.; Piatko, Christine D.; Silverman, Ruth; Wu, Angela Y. (2002). "An efficient k-means clustering algorithm: Analysis and implementation" (PDF). IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (7): 881–892. doi:10.1109/TPAMI.2002.1017616. S2CID 12003435. Retrieved 2009-04-24.
Dhillon, I. S.; Modha, D. M. (2001). "Concept decompositions for large sparse text data using clustering". Machine Learning. 42 (1): 143–175. doi:10.1023/a:1007612920971.
Amorim, R. C.; Mirkin, B. (2012). "Minkowski Metric, Feature Weighting and Anomalous Cluster Initialisation in k-Means Clustering". Pattern Recognition. 45 (3): 1061–1075. doi:10.1016/j.patcog.2011.08.012.
Amorim, R. C.; Hennig, C. (2015). "Recovering the number of clusters in data sets with noise features using feature rescaling factors". Information Sciences. 324: 126–145. arXiv:1602.06989. doi:10.1016/j.ins.2015.06.039. S2CID 315803.
Piccialli, Veronica; Sudoso, Antonio M.; Wiegele, Angelika (2022-03-28). "SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering". INFORMS Journal on Computing. 34 (4): 2144–2162. arXiv:2104.11542. doi:10.1287/ijoc.2022.1166. ISSN 1091-9856. S2CID 233388043.
Bagirov, A. M.; Taheri, S.; Ugon, J. (2016). "Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems". Pattern Recognition. 53: 12–24. Bibcode:2016PatRe..53...12B. doi:10.1016/j.patcog.2015.11.011.
Fränti, Pasi (2018). "Efficiency of random swap clustering". Journal of Big Data. 5 (1): 1–21. doi:10.1186/s40537-018-0122-y.
Hansen, P.; Mladenovic, N. (2001). "J-Means: A new local search heuristic for minimum sum of squares clustering". Pattern Recognition. 34 (2): 405–413. Bibcode:2001PatRe..34..405H. doi:10.1016/S0031-3203(99)00216-2.
Krishna, K.; Murty, M. N. (1999). "Genetic k-means algorithm". IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. 29 (3): 433–439. doi:10.1109/3477.764879. PMID 18252317.
Gribel, Daniel; Vidal, Thibaut (2019). "HG-means: A scalable hybrid metaheuristic for minimum sum-of-squares clustering". Pattern Recognition. 88: 569–583. arXiv:1804.09813. doi:10.1016/j.patcog.2018.12.022. S2CID 13746584.
Schwenker, Friedhelm; Kestler, Hans A.; Palm, Günther (2001). "Three learning phases for radial-basis-function networks". Neural Networks. 14 (4–5): 439–458. CiteSeerX 10.1.1.109.312. doi:10.1016/s0893-6080(01)00027-2. PMID 11411631.
Aharon, Michal; Elad, Michael; Bruckstein, Alfred (2006). "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation" (PDF). IEEE Transactions on Signal Processing. 54 (11): 4311. Bibcode:2006ITSP...54.4311A. doi:10.1109/TSP.2006.881199. S2CID 7477309.
Drineas, Petros; Frieze, Alan M.; Kannan, Ravi; Vempala, Santosh; Vinay, Vishwanathan (2004). "Clustering large graphs via the singular value decomposition" (PDF). Machine Learning. 56 (1–3): 9–33. doi:10.1023/b:mach.0000033113.59016.96. S2CID 5892850. Retrieved 2012-08-02.
Little, Max A.; Jones, Nick S. (2011). "Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory". Proceedings of the Royal Society A. 467 (2135): 3088–3114. Bibcode:2011RSPSA.467.3088L. doi:10.1098/rspa.2010.0671. PMC 3191861. PMID 22003312.

gatech.edu

cc.gatech.edu

Drineas, Petros; Frieze, Alan M.; Kannan, Ravi; Vempala, Santosh; Vinay, Vishwanathan (2004). "Clustering large graphs via the singular value decomposition" (PDF). Machine Learning. 56 (1–3): 9–33. doi:10.1023/b:mach.0000033113.59016.96. S2CID 5892850. Retrieved 2012-08-02.

harvard.edu

ui.adsabs.harvard.edu

Bagirov, A. M.; Taheri, S.; Ugon, J. (2016). "Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems". Pattern Recognition. 53: 12–24. Bibcode:2016PatRe..53...12B. doi:10.1016/j.patcog.2015.11.011.
Hansen, P.; Mladenovic, N. (2001). "J-Means: A new local search heuristic for minimum sum of squares clustering". Pattern Recognition. 34 (2): 405–413. Bibcode:2001PatRe..34..405H. doi:10.1016/S0031-3203(99)00216-2.
Aharon, Michal; Elad, Michael; Bruckstein, Alfred (2006). "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation" (PDF). IEEE Transactions on Signal Processing. 54 (11): 4311. Bibcode:2006ITSP...54.4311A. doi:10.1109/TSP.2006.881199. S2CID 7477309.
Little, Max A.; Jones, Nick S. (2011). "Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory". Proceedings of the Royal Society A. 467 (2135): 3088–3114. Bibcode:2011RSPSA.467.3088L. doi:10.1098/rspa.2010.0671. PMC 3191861. PMID 22003312.

huji.ac.il

cs.huji.ac.il

Vinnikov, Alon; Shalev-Shwartz, Shai (2014). "K-means Recovers ICA Filters when Independent Components are Sparse" (PDF). Proceedings of the International Conference on Machine Learning (ICML 2014).

icml.cc

Kulis, Brian; Jordan, Michael I. (2012-06-26). "Revisiting k-means: new algorithms via Bayesian nonparametrics" (PDF). ICML. Association for Computing Machinery. pp. 1131–1138. ISBN 9781450312851.

iitk.ac.in

gautam5.cse.iitk.ac.in

Bhowmick, Abhishek (2009). "A theoretical analysis of Lloyd's algorithm for k-means clustering" (PDF). Archived from the original (PDF) on 2015-12-08. See also here.

informs.org

pubsonline.informs.org

Piccialli, Veronica; Sudoso, Antonio M.; Wiegele, Angelika (2022-03-28). "SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering". INFORMS Journal on Computing. 34 (4): 2144–2162. arXiv:2104.11542. doi:10.1287/ijoc.2022.1166. ISSN 1091-9856. S2CID 233388043.

jstor.org

Forgy, Edward W. (1965). "Cluster analysis of multivariate data: efficiency versus interpretability of classifications". Biometrics. 21 (3): 768–769. JSTOR 2528559.
Hartigan, J. A.; Wong, M. A. (1979). "Algorithm AS 136: A k-Means Clustering Algorithm". Journal of the Royal Statistical Society, Series C. 28 (1): 100–108. JSTOR 2346830.

le.ac.uk

math.le.ac.uk

Mirkes, E. M. "K-means and k-medoids applet". Retrieved 2 January 2016.

mit.edu

people.csail.mit.edu

Hamerly, Greg; Elkan, Charles (2002). "Alternatives to the k-means algorithm that find better clusterings" (PDF). Proceedings of the eleventh international conference on Information and knowledge management (CIKM).

mlr.press

proceedings.mlr.press

Telgarsky, Matus. "Hartigan's Method: k-means Clustering without Voronoi" (PDF).

mpg.de

opt.kyb.tuebingen.mpg.de

Drake, Jonathan (2012). "Accelerated k-means with adaptive distance bounds" (PDF). The 5th NIPS Workshop on Optimization for Machine Learning, OPT2012.

nih.gov

pubmed.ncbi.nlm.nih.gov

Krishna, K.; Murty, M. N. (1999). "Genetic k-means algorithm". IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. 29 (3): 433–439. doi:10.1109/3477.764879. PMID 18252317.
Schwenker, Friedhelm; Kestler, Hans A.; Palm, Günther (2001). "Three learning phases for radial-basis-function networks". Neural Networks. 14 (4–5): 439–458. CiteSeerX 10.1.1.109.312. doi:10.1016/s0893-6080(01)00027-2. PMID 11411631.
Little, Max A.; Jones, Nick S. (2011). "Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory". Proceedings of the Royal Society A. 467 (2135): 3088–3114. Bibcode:2011RSPSA.467.3088L. doi:10.1098/rspa.2010.0671. PMC 3191861. PMID 22003312.

ncbi.nlm.nih.gov

Little, Max A.; Jones, Nick S. (2011). "Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory". Proceedings of the Royal Society A. 467 (2135): 3088–3114. Bibcode:2011RSPSA.467.3088L. doi:10.1098/rspa.2010.0671. PMC 3191861. PMID 22003312.

nips.cc

papers.nips.cc

Hamerly, Greg; Elkan, Charles (2004). "Learning the k in k-means" (PDF). Advances in Neural Information Processing Systems. 16: 281.

nrbook.com

apps.nrbook.com

Press, W. H.; Teukolsky, S. A.; Vetterling, W. T.; Flannery, B. P. (2007). "Section 16.1. Gaussian Mixture Models and k-Means Clustering". Numerical Recipes: The Art of Scientific Computing (3rd ed.). New York (NY): Cambridge University Press. ISBN 978-0-521-88068-8.

projecteuclid.org

MacQueen, J. B. (1967). Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. Vol. 1. University of California Press. pp. 281–297. MR 0214227. Zbl 0214.46201. Retrieved 2009-04-07.

psu.edu

citeseerx.ist.psu.edu

Lloyd, Stuart P. (1957). "Least square quantization in PCM". Bell Telephone Laboratories Paper. Published in journal much later: Lloyd, Stuart P. (1982). "Least squares quantization in PCM" (PDF). IEEE Transactions on Information Theory. 28 (2): 129–137. CiteSeerX 10.1.1.131.1338. doi:10.1109/TIT.1982.1056489. S2CID 10833328. Retrieved 2009-04-15.
Schwenker, Friedhelm; Kestler, Hans A.; Palm, Günther (2001). "Three learning phases for radial-basis-function networks". Neural Networks. 14 (4–5): 439–458. CiteSeerX 10.1.1.109.312. doi:10.1016/s0893-6080(01)00027-2. PMID 11411631.

researchgate.net

Bhowmick, Abhishek (2009). "A theoretical analysis of Lloyd's algorithm for k-means clustering" (PDF). Archived from the original (PDF) on 2015-12-08. See also here.
Krishna, K.; Murty, M. N. (1999). "Genetic k-means algorithm". IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. 29 (3): 433–439. doi:10.1109/3477.764879. PMID 18252317.

semanticscholar.org

api.semanticscholar.org

Kriegel, Hans-Peter; Schubert, Erich; Zimek, Arthur (2016). "The (black) art of runtime evaluation: Are we comparing algorithms or implementations?". Knowledge and Information Systems. 52 (2): 341–378. doi:10.1007/s10115-016-1004-2. ISSN 0219-1377. S2CID 40772241.
Lloyd, Stuart P. (1957). "Least square quantization in PCM". Bell Telephone Laboratories Paper. Published in journal much later: Lloyd, Stuart P. (1982). "Least squares quantization in PCM" (PDF). IEEE Transactions on Information Theory. 28 (2): 129–137. CiteSeerX 10.1.1.131.1338. doi:10.1109/TIT.1982.1056489. S2CID 10833328. Retrieved 2009-04-15.
Pelleg, Dan; Moore, Andrew (1999). "Accelerating exact k -means algorithms with geometric reasoning". Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. San Diego, California, United States: ACM Press. pp. 277–281. doi:10.1145/312129.312248. ISBN 9781581131437. S2CID 13907420.
Celebi, M. E.; Kingravi, H. A.; Vela, P. A. (2013). "A comparative study of efficient initialization methods for the k-means clustering algorithm". Expert Systems with Applications. 40 (1): 200–210. arXiv:1209.1960. doi:10.1016/j.eswa.2012.07.021. S2CID 6954668.
Vattani, A. (2011). "k-means requires exponentially many iterations even in the plane" (PDF). Discrete and Computational Geometry. 45 (4): 596–616. doi:10.1007/s00454-011-9340-1. S2CID 42683406.
Dasgupta, S.; Freund, Y. (July 2009). "Random Projection Trees for Vector Quantization". IEEE Transactions on Information Theory. 55 (7): 3229–42. arXiv:0805.1390. doi:10.1109/TIT.2009.2021326. S2CID 666114.
Arthur, David; Vassilvitskii, Sergei (2006-01-01). "How slow is the k -means method?". Proceedings of the twenty-second annual symposium on Computational geometry. SCG '06. ACM. pp. 144–153. doi:10.1145/1137856.1137880. ISBN 978-1595933409. S2CID 3084311.
Kanungo, Tapas; Mount, David M.; Netanyahu, Nathan S.; Piatko, Christine D.; Silverman, Ruth; Wu, Angela Y. (2002). "An efficient k-means clustering algorithm: Analysis and implementation" (PDF). IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (7): 881–892. doi:10.1109/TPAMI.2002.1017616. S2CID 12003435. Retrieved 2009-04-24.
Amorim, R. C.; Hennig, C. (2015). "Recovering the number of clusters in data sets with noise features using feature rescaling factors". Information Sciences. 324: 126–145. arXiv:1602.06989. doi:10.1016/j.ins.2015.06.039. S2CID 315803.
Piccialli, Veronica; Sudoso, Antonio M.; Wiegele, Angelika (2022-03-28). "SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering". INFORMS Journal on Computing. 34 (4): 2144–2162. arXiv:2104.11542. doi:10.1287/ijoc.2022.1166. ISSN 1091-9856. S2CID 233388043.
Gribel, Daniel; Vidal, Thibaut (2019). "HG-means: A scalable hybrid metaheuristic for minimum sum-of-squares clustering". Pattern Recognition. 88: 569–583. arXiv:1804.09813. doi:10.1016/j.patcog.2018.12.022. S2CID 13746584.
Aharon, Michal; Elad, Michael; Bruckstein, Alfred (2006). "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation" (PDF). IEEE Transactions on Signal Processing. 54 (11): 4311. Bibcode:2006ITSP...54.4311A. doi:10.1109/TSP.2006.881199. S2CID 7477309.
Drineas, Petros; Frieze, Alan M.; Kannan, Ravi; Vempala, Santosh; Vinay, Vishwanathan (2004). "Clustering large graphs via the singular value decomposition" (PDF). Machine Learning. 56 (1–3): 9–33. doi:10.1023/b:mach.0000033113.59016.96. S2CID 5892850. Retrieved 2012-08-02.

stanford.edu

cs.stanford.edu

Coates, Adam; Ng, Andrew Y. (2012). "Learning feature representations with k-means" (PDF). In Montavon, G.; Orr, G. B.; Müller, K.-R. (eds.). Neural Networks: Tricks of the Trade. Springer.

stanford.edu

Coates, Adam; Lee, Honglak; Ng, Andrew Y. (2011). An analysis of single-layer networks in unsupervised feature learning (PDF). International Conference on Artificial Intelligence and Statistics (AISTATS). Archived from the original (PDF) on 2013-05-10.

technion.ac.il

cs.technion.ac.il

Aharon, Michal; Elad, Michael; Bruckstein, Alfred (2006). "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation" (PDF). IEEE Transactions on Signal Processing. 54 (11): 4311. Bibcode:2006ITSP...54.4311A. doi:10.1109/TSP.2006.881199. S2CID 7477309.

toronto.edu

cs.toronto.edu

Lloyd, Stuart P. (1957). "Least square quantization in PCM". Bell Telephone Laboratories Paper. Published in journal much later: Lloyd, Stuart P. (1982). "Least squares quantization in PCM" (PDF). IEEE Transactions on Information Theory. 28 (2): 129–137. CiteSeerX 10.1.1.131.1338. doi:10.1109/TIT.1982.1056489. S2CID 10833328. Retrieved 2009-04-15.

ucsd.edu

cseweb.ucsd.edu

Vattani, A. (2011). "k-means requires exponentially many iterations even in the plane" (PDF). Discrete and Computational Geometry. 45 (4): 596–616. doi:10.1007/s00454-011-9340-1. S2CID 42683406.

www-cse.ucsd.edu

Elkan, Charles (2003). "Using the triangle inequality to accelerate k-means" (PDF). Proceedings of the Twentieth International Conference on Machine Learning (ICML).

uef.fi

cs.uef.fi

Pelleg, D.; & Moore, A. W. (2000, June). "X-means: Extending k-means with Efficient Estimation of the Number of Clusters". In ICML, Vol. 1

umd.edu

cs.umd.edu

Kanungo, Tapas; Mount, David M.; Netanyahu, Nathan S.; Piatko, Christine D.; Silverman, Ruth; Wu, Angela Y. (2002). "An efficient k-means clustering algorithm: Analysis and implementation" (PDF). IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (7): 881–892. doi:10.1109/TPAMI.2002.1017616. S2CID 12003435. Retrieved 2009-04-24.

uta.edu

ranger.uta.edu

Zha, Hongyuan; Ding, Chris; Gu, Ming; He, Xiaofeng; Simon, Horst D. (December 2001). "Spectral Relaxation for k-means Clustering" (PDF). Neural Information Processing Systems Vol.14 (NIPS 2001): 1057–1064.
Ding, Chris; He, Xiaofeng (July 2004). "K-means Clustering via Principal Component Analysis" (PDF). Proceedings of International Conference on Machine Learning (ICML 2004): 225–232.

web.archive.org

Bhowmick, Abhishek (2009). "A theoretical analysis of Lloyd's algorithm for k-means clustering" (PDF). Archived from the original (PDF) on 2015-12-08. See also here.
Coates, Adam; Lee, Honglak; Ng, Andrew Y. (2011). An analysis of single-layer networks in unsupervised feature learning (PDF). International Conference on Artificial Intelligence and Statistics (AISTATS). Archived from the original (PDF) on 2013-05-10.

worldcat.org

search.worldcat.org

Kriegel, Hans-Peter; Schubert, Erich; Zimek, Arthur (2016). "The (black) art of runtime evaluation: Are we comparing algorithms or implementations?". Knowledge and Information Systems. 52 (2): 341–378. doi:10.1007/s10115-016-1004-2. ISSN 0219-1377. S2CID 40772241.
Manning, Christopher D.; Raghavan, Prabhakar; Schütze, Hinrich (2008). Introduction to information retrieval. Cambridge University Press. ISBN 978-0521865715. OCLC 190786122.
Piccialli, Veronica; Sudoso, Antonio M.; Wiegele, Angelika (2022-03-28). "SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering". INFORMS Journal on Computing. 34 (4): 2144–2162. arXiv:2104.11542. doi:10.1287/ijoc.2022.1166. ISSN 1091-9856. S2CID 233388043.
Kevin P. Murphy (2012). Machine learning : a probabilistic perspective. Cambridge, Mass.: MIT Press. ISBN 978-0-262-30524-2. OCLC 810414751.

zbmath.org

MacQueen, J. B. (1967). Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. Vol. 1. University of California Press. pp. 281–297. MR 0214227. Zbl 0214.46201. Retrieved 2009-04-07.
Steinhaus, Hugo (1957). "Sur la division des corps matériels en parties". Bull. Acad. Polon. Sci. (in French). 4 (12): 801–804. MR 0090073. Zbl 0079.16403.