\begin{thebibliography}{} \bibitem[Achlioptas and McSherry, 2005]{achlioptas:05mixtures} Achlioptas, D. and McSherry, F. (2005). \newblock On spectral learning of mixtures of distributions. \newblock In Auer, P. and Meir, R., editors, {\em 18th Annual Conference on Learning Theory, COLT 2005}, pages 458--471, Berlin/Heidelberg. Springer. \bibitem[Arora and Kannan, 2001]{arora:01} Arora, S. and Kannan, R. (2001). \newblock Learning mixtures of arbitrary gaussians. \newblock In {\em STOC '01: Proceedings of the thirty-third annual ACM symposium on Theory of computing}, pages 247--257, New York, NY, USA. ACM Press. \bibitem[Banfield and Raftery, 1993]{banfield:93} Banfield, J.~D. and Raftery, A.~E. (1993). \newblock Model-based gaussian and non-gaussian clustering. \newblock {\em Biometrics}, 49:803--821. \bibitem[Bradley and Mangasarian, 2005]{bradley:05} Bradley, P. and Mangasarian, O. (2005). \newblock Clustering via concave minimization. \newblock In {\em Advances in Neural Information Processing systems (NIPS)}, Cambridge, MA. MIT Press. \bibitem[Bubeck et~al., 2009]{MBubeckLuxburg:tr-kmeans-ini09} Bubeck, S., Meil\u{a}, M., and von Luxburg, U. (2009). \newblock How the initialization affects the stability of the k-means algorithm. \newblock Technical Report arXiv:0907.5494v1 [stat.ML], ArXiv. \bibitem[{Carreira-Perpinan}, 2007]{carreira-perp:07} {Carreira-Perpinan}, M.~A. (2007). \newblock Gaussian mean shift is an {EM} algorithm. \newblock {\em IEEE Trans. on Pattern Analysis and Machine Intelligence}, 29(5):767--776. \bibitem[Dasgupta, 2000]{Dasgupta:00random} Dasgupta, S. (2000). \newblock Experiments with random projection. \newblock In {\em UAI '00: Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence}, pages 143--151, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc. \bibitem[Dasgupta and Gupta, 2002]{dasgupta:02} Dasgupta, S. and Gupta, A. (2002). \newblock An elementary proof of a theorem of johnson and lindenstrauss. \newblock {\em Algorithms}, 22:60--65. \bibitem[Dasgupta and Schulman, 2007]{dasgupta:07} Dasgupta, S. and Schulman, L. (2007). \newblock A probabilistic analysis of em for mixtures of separated, spherical gaussians. \newblock {\em Journal of Machine Learnig Research}, 8:203--226. \bibitem[Har-Peled and Mazumdar, 2004]{har-peled:04} Har-Peled, S. and Mazumdar, S. (2004). \newblock Coresets for k-means and k-median clustering and their applications. \newblock In {\em Proc. 36th Annu. ACM Sympos. Theory Comput (STOC)}, pages 291--300. \bibitem[Hochbaum and Shmoys, 1985]{hochbaum:85} Hochbaum, D.~S. and Shmoys, D.~B. (1985). \newblock A best possible heuristic for the k-center problem. \newblock {\em Mathematics of Operations Research}, 10(2):180--184. \bibitem[Lloyd, 1982]{lloyd:82} Lloyd, S.~P. (1982). \newblock Least squares quantization in {PCM}. \newblock {\em IEEE Transactions on Information Theory}, 28:129--137. \bibitem[McLachlan and Krishnan, 1997]{McLachlan:97} McLachlan, G.~J. and Krishnan, T. (1997). \newblock {\em The EM algorithm and extensions}. \newblock Wiley, New York, NY. \bibitem[Neal and Hinton, 1998]{neal:98} Neal, R.~M. and Hinton, G.~E. (1998). \newblock A view of the em algorithm that justifies incremental, sparse, and other variants. \newblock In Jordan, M.~I., editor, {\em Learning in Graphical Models}, NATO Science series, pages 355--368. Kluwer Academic Publishers. \bibitem[Nugent and Meila, 2010]{NugentM:clust-bookchapter10} Nugent, R. and Meila, M. (2010). \newblock {\em Statistical Methods in Molecular Biology}, chapter An Overview of Clustering Applied to Molecular Biology. \newblock Humana Press, Springer. \bibitem[Srebro et~al., 2006]{srebro:06} Srebro, N., Shakhnarovich, G., and Roweis, S. (2006). \newblock An investigation of computational and informational limits in gaussian mixture clustering. \newblock In {\em Proceedings of the 23rd International Conference on Machine Learning (ICML)}. \bibitem[Vempala and Wang, 2004]{vempala:04mixtures} Vempala, S. and Wang, G. (2004). \newblock A spectral algorithm for learning mixtures of distributions. \newblock {\em Journal of Computer Systems Science}, 68(4):841--860. \end{thebibliography}