K-means++ under approximation stability

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7876 LNCS, Issue , 2013, Pages 84-95

  Agarwal, Manu ^a   Jaiswal, Ragesh ^b   Pal, Arindam ^c  

^a INDIAN INSTITUTE OF TECHNOLOGY JODHPUR   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^c TATA CONSULTANCY SERVICES   (India)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; COMPUTATION THEORY; LEARNING ALGORITHMS; OPTIMIZATION; PROBABILITY;

K-MEANS CLUSTERING; LLOYD'S ALGORITHMS; PERFORMANCE GUARANTEES; PROBABILITY PROPORTIONAL; SAMPLING ALGORITHM; SEPARATION CONDITION; STABILITY CONDITION; UNDER-APPROXIMATION;

CLUSTERING ALGORITHMS;

EID: 84893438604     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38236-9_9     Document Type: Conference Paper

References (9)

1. Aggarwal, A., Deshpande, A., Kannan, R.: Adaptive sampling for k-means clustering. In: Dinur, I., Jansen, K., Naor, J., Rolim, J. (eds.) APPROX and RANDOM 2009. LNCS, Vol. 5687, pp. 15-28. Springer, Heidelberg (2009)
2. Ailon, N., Jaiswal, R., Monteleoni, C.: Streaming k-means approximation. In: Advances in Neural Information Processing Systems (NIPS 2009), pp. 10-18 (2009)
3. Arthur, D., Vassilvitskii, S.: k-means++: the advantages of careful seeding. In: In Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2007), pp. 1027-1035 (2007)
4. Awasthi, P., Blum, A., Sheffet, O.: Stability yields a PTAS for k-median and k-means clustering. In: Proceedings of the 51st Annual IEEE Symposium on Foundations of Computer Science (FOCS 2010), pp. 309-318 (2010)
5. Balcan, M.-F., Blum, A., Gupta, A.: Approximate clustering without the approximation. In: Proceedings of the 20th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2009), pp. 1068-1077 (2009)
6. Brunsch, T., Röglin, H.: A bad instance for k-means++. In: Ogihara, M., Tarui, J. (eds.) TAMC 2011. LNCS, Vol. 6648, pp. 344-352. Springer, Heidelberg (2011)
7. Jaiswal, R., Garg, N.: Analysis of k-means++ for separable data. In: Proceedings of the 16th International Workshop on Randomization and Computation, pp. 591-602 (2012)
8. 2-sampling based PTAS for k-means and other Clustering Problems. In: Gudmundsson, J., Mestre, J., Viglas, T. (eds.) COCOON 2012. LNCS, Vol. 7434, pp. 13-24. Springer, Heidelberg (2012)
9. Ostrovsky, R., Rabani, Y., Schulman, L.J., Swamy, C.: The effectiveness of lloyd-type methods for the k-means problem. In: Proceedings of the 47th IEEE FOCS, pp. 165-176 (2006)