อ้างอิง ของ การแบ่งกลุ่มข้อมูลแบบค่าเฉลี่ย k

  1. ↑ 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. สืบค้นเมื่อ 2009-04-07.
  2. ↑ Steinhaus, H. (1957). "Sur la division des corps matériels en parties". Bull. Acad. Polon. Sci. (ภาษาฝรั่งเศส). 4 (12): 801–804. MR 0090073. Zbl 0079.16403.
  3. ↑ Lloyd, S. P. (1957). "Least square quantization in PCM". Bell Telephone Laboratories Paper. Published in journal much later:Lloyd., S. P. (1982). "Least squares quantization in PCM" (PDF). IEEE Transactions on Information Theory. 28 (2): 129–137. doi:10.1109/TIT.1982.1056489. สืบค้นเมื่อ 2009-04-15.
  4. ↑ E.W. Forgy (1965). "Cluster analysis of multivariate data: efficiency versus interpretability of classifications". Biometrics. 21: 768–769.
  5. ↑ J.A. Hartigan (1975). Clustering algorithms. John Wiley & Sons.
  6. ↑ MacKay, David (2003). "Chapter 20. An Example Inference Task: Clustering" (PDF). Information Theory, Inference and Learning Algorithms. Cambridge University Press. pp. 284–292. ISBN 0-521-64298-1. MR 2012999.
  7. ↑ Since the square root is a monotone function, this also is the minimum Euclidean distance assignment.
  8. ↑ 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.
  9. 1 2 Hamerly, G.; Elkan, C. (2002). Alternatives to the k-means algorithm that find better clusterings (PDF). Proceedings of the eleventh international conference on Information and knowledge management (CIKM). คลังข้อมูลเก่าเก็บจากแหล่งเดิม (PDF)เมื่อ 5 สิงหาคม 2012. สืบค้นเมื่อ 27 เมษายน 2015.
  10. ↑ Vattani., A. (2011). "k-means requires exponentially many iterations even in the plane" (PDF). Discrete & Computational Geometry. 45 (4): 596–616. doi:10.1007/s00454-011-9340-1.
  11. 1 2 Arthur, D.; Manthey, B.; Roeglin, H. (2009). k-means has polynomial smoothed complexity. Proceedings of the 50th Symposium on Foundations of Computer Science (FOCS).
  12. ↑ Aloise, D.; Deshpande, A.; Hansen, P.; Popat, P. (2009). "NP-hardness of Euclidean sum-of-squares clustering". Machine Learning. 75: 245–249. doi:10.1007/s10994-009-5103-0.
  13. ↑ Dasgupta, S.; Freund, Y. (กรกฎาคม 2009). "Random Projection Trees for Vector Quantization". Information Theory, IEEE Transactions on. 55: 3229–3242. arXiv:0805.1390. doi:10.1109/TIT.2009.2021326.
  14. ↑ Mahajan, M.; Nimbhorkar, P.; Varadarajan, K. (2009). "The Planar k-Means Problem is NP-Hard". Lecture Notes in Computer Science. 5431: 274–285. doi:10.1007/978-3-642-00202-1_24.
  15. ↑ 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. 332–339. doi:10.1145/177424.178042.
  16. ↑ Chatti Subbalakshmia; P. Venkateswara Raob; S. Krishna Mohan Rao (2014). "Performance Issues on K-Mean Partitioning Clustering Algorithm". International Journal of Computer (IJC). 14 (1): 41–51. ISSN 2307-4531.
  17. ↑ Kanungo, T.; Mount, D. M.; Netanyahu, N. S.; Piatko, C. D.; Silverman, R.; Wu, A. Y. (2002). "An efficient k-means clustering algorithm: Analysis and implementation" (PDF). IEEE Trans. Pattern Analysis and Machine Intelligence. 24: 881–892. doi:10.1109/TPAMI.2002.1017616. สืบค้นเมื่อ 2009-04-24.
  18. ↑ Gereon Frahling; Christian Sohler (5 ธันวาคม 2005). A fast k-means implementation using coresets (PDF). Proceedings of the twenty-second annual symposium on Computational geometry (SoCG). S2CID 5891336.
  19. ↑ Elkan, C. (2003). Using the triangle inequality to accelerate k-means (PDF). Proceedings of the Twentieth International Conference on Machine Learning (ICML).
  20. ↑ 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.
  21. ↑ Dhillon, I. S.; Modha, D. M. (2001). "Concept decompositions for large sparse text data using clustering". Machine Learning. 42 (1): 143–175.
  22. ↑ Amorim, R. C.; Mirkin, B (2012). "Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering". Pattern Recognition. 45 (3): 1061–1075. doi:10.1016/j.patcog.2011.08.012.
  23. 1 2 3 Coates, Adam; Ng, Andrew Y. (2012). "Learning feature representations with k-means" (PDF). ใน Grégoire Montavon; และคณะ (บ.ก.). Neural Networks: Tricks of the Trade. Springer. ISBN 978-3-642-35289-8. คลังข้อมูลเก่าเก็บจากแหล่งเดิม (PDF)เมื่อ 6 มิถุนายน 2013. สืบค้นเมื่อ 25 เมษายน 2015.
  24. ↑ 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.
  25. 1 2 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). คลังข้อมูลเก่าเก็บจากแหล่งเดิม (PDF)เมื่อ 10 พฤษภาคม 2013. สืบค้นเมื่อ 25 เมษายน 2015.
  26. ↑ Lin, Dekang; Wu, Xiaoyun (2009). Phrase clustering for discriminative learning (PDF). Annual Meeting of the ACL and IJCNLP. pp. 1030–1038.
  27. ↑ Press, WH; Teukolsky, SA; Vetterling, WT; Flannery, BP (2007). "Section 16.1. Gaussian Mixture Models and k-Means Clustering". Numerical Recipes: The Art of Scientific Computing (3 ed.). New York: Cambridge University Press. ISBN 978-0-521-88068-8. คลังข้อมูลเก่าเก็บจากแหล่งเดิมเมื่อ 2011-08-11. สืบค้นเมื่อ 2015-04-27.
  28. ↑ Aharon, Michal; Elad, Michael; Bruckstein, Alfred (พฤศจิกายน 2006). "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation" (PDF). IEEE Transactions on Signal Processing. 54 (11): 4311–22. คลังข้อมูลเก่าเก็บจากแหล่งเดิม (PDF)เมื่อ 20 มิถุนายน 2013. สืบค้นเมื่อ 27 เมษายน 2015.
  29. 1 2 Little, M.A.; Jones, N.S. (2011). "Generalized Methods and Solvers for Piecewise Constant Signals: Part I" (PDF). Proceedings of the Royal Society A.
  30. ↑ H. Zha; C. Ding; M. Gu; X. He; H.D. Simon (ธันวาคม 2001). "Spectral Relaxation for K-means Clustering" (PDF). Neural Information Processing Systems vol.14 (NIPS 2001). Vancouver, Canada: 1057–1064.
  31. ↑ Chris Ding; Xiaofeng He (กรกฎาคม 2004). K-means Clustering via Principal Component Analysis (PDF). Proc. of Int'l Conf. Machine Learning (ICML 2004). pp. 225–232.
  32. ↑ P. Drineas; A. Frieze; R. Kannan; S. Vempala; V. Vinay (2004). "Clustering large graphs via the singular value decomposition" (PDF). Machine learning. 56: 9–33. doi:10.1023/b:mach.0000033113.59016.96. สืบค้นเมื่อ 2 สิงหาคม 2012.
  33. ↑ M. Cohen; S. Elder; C. Musco; C. Musco; M. Persu (2014). "Dimensionality reduction for k-means clustering and low rank approximation (Appendix B)". arXiv:1410.6801v3.
  34. ↑ Vinnikov, Alon; Shalev-Shwartz, Shai (2014). K-means Recovers ICA Filters when Independent Components are Sparse (PDF). Proc. of Int'l Conf. Machine Learning (ICML 2014) (ภาษาอังกฤษ).

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