Approximate K-Means++ in Sublinear Time
暂无分享,去创建一个
Andreas Krause | Olivier Bachem | Mario Lucic | S. Hamed Hassani | Andreas Krause | Mario Lucic | Olivier Bachem | S. Hassani
[1] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[2] Ankit Aggarwal,et al. Adaptive Sampling for k-Means Clustering , 2009, APPROX-RANDOM.
[3] Michael I. Jordan,et al. Revisiting k-means: New Algorithms via Bayesian Nonparametrics , 2011, ICML.
[4] Nitin Garg,et al. Analysis of k-Means++ for Separable Data , 2012, APPROX-RANDOM.
[5] Qing He,et al. Parallel K-Means Clustering Based on MapReduce , 2009, CloudCom.
[6] Andreas Krause,et al. The next big one: Detecting earthquakes and other rare events from community-based sensors , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.
[7] Sergei Vassilvitskii,et al. k-means++: the advantages of careful seeding , 2007, SODA '07.
[8] Honglak Lee,et al. An Analysis of Single-Layer Networks in Unsupervised Feature Learning , 2011, AISTATS.
[9] Adam Meyerson,et al. Fast and Accurate k-means For Large Datasets , 2011, NIPS.
[10] Sudipto Guha,et al. Clustering Data Streams: Theory and Practice , 2003, IEEE Trans. Knowl. Data Eng..
[11] Klaus Jansen,et al. Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques , 2006, Lecture Notes in Computer Science.
[12] Ragesh Jaiswal,et al. Improved analysis of D2-sampling based PTAS for k-means and other clustering problems , 2015, Inf. Process. Lett..
[13] Heiko Röglin,et al. A bad instance for k-means++ , 2011, Theor. Comput. Sci..
[14] Andrew Y. Ng,et al. Learning Feature Representations with K-Means , 2012, Neural Networks: Tricks of the Trade.
[15] Thierry Bertin-Mahieux,et al. The Million Song Dataset , 2011, ISMIR.
[16] D. Pollard. Strong Consistency of $K$-Means Clustering , 1981 .
[17] Amit Kumar,et al. A Simple D 2-Sampling Based PTAS for k-Means and other Clustering Problems , 2012, COCOON.
[18] Yoshua Bengio,et al. Convergence Properties of the K-Means Algorithms , 1994, NIPS.
[19] Philip S. Yu,et al. Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.
[20] D. Sculley,et al. Web-scale k-means clustering , 2010, WWW '10.
[21] Manu Agarwal,et al. k-Means++ under approximation stability , 2015, Theor. Comput. Sci..
[22] Maria-Florina Balcan,et al. Approximate clustering without the approximation , 2009, SODA.
[23] Amit Kumar,et al. A Simple D2-Sampling Based PTAS for k-Means and Other Clustering Problems , 2012, Algorithmica.
[24] Sergei Vassilvitskii,et al. Scalable K-Means++ , 2012, Proc. VLDB Endow..
[25] Christian Sohler,et al. StreamKM++: A clustering algorithm for data streams , 2010, JEAL.
[26] Exact bound for the convergence of metropolis chains , 2000 .
[27] Nir Ailon,et al. Streaming k-means approximation , 2009, NIPS.
[28] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[29] Andreas Krause,et al. Coresets for Nonparametric Estimation - the Case of DP-Means , 2015, ICML.
[30] Rafail Ostrovsky,et al. Streaming k-means on well-clusterable data , 2011, SODA '11.