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Data stream clustering
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1	MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering. Albert Bifet1 , Geoff Holmes1 , Bernhard Pfahringer1 , Philipp Kranen2 , Hardy Kremer2 , Timm Jansen2 , and Thomas Seidl2 1 Add to Reading List Source URL: moa.cs.waikato.ac.nz Language: English - Date: 2014-11-07 23:43:25 Data mining Statistics Computational statistics Software Machine learning Massive Online Analysis Cluster analysis Formal sciences Data stream mining K-means clustering Concept drift Weka
2	Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner Add to Reading List Source URL: eew.caltech.edu Language: English - Date: 2012-05-15 11:47:37 Statistics Probability Maximum likelihood estimation Probability distributions Bayesian statistics Expectationmaximization algorithm Mixture model Normal distribution K-means clustering Likelihood function Data stream clustering Gamma distribution
3	CS264: Beyond Worst-Case Analysis Lecture #6: Clustering in Approximation-Stable Instances∗ Tim Roughgarden† October 10, 2014 Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2015-01-06 18:13:07 Statistics Computational statistics Data analysis Cluster analysis Data mining Geostatistics K-means clustering K-medians clustering Approximation algorithm Median Data stream clustering Single-linkage clustering
4	Ulaş Ayaz ICERM, Brown University Subspace Clustering with Ordered Weighted L1 Minimization Add to Reading List Source URL: math.nyu.edu Language: English - Date: 2015-04-28 13:15:21 Cluster analysis Image segmentation Statistics Computational statistics Data analysis Data stream clustering
5	Clustering Aggregation ARISTIDES GIONIS Yahoo! Research Labs, Barcelona HEIKKI MANNILA University of Helsinki and Helsinki University of Technology and Add to Reading List Source URL: www.cs.uoi.gr Language: English - Date: 2011-11-03 16:38:34 Cluster analysis Consensus clustering Correlation clustering K-means clustering Data stream clustering K-means++
6	Parallelizing Clustering of Geoscientific Data Sets using Data Streams Silvia Nittel Spatial Information Science & Engineering University of Maine Orono, ME, USA Add to Reading List Source URL: silvianittel.files.wordpress.com Language: English - Date: 2016-07-10 13:05:33 K-means clustering Cluster analysis Vector quantization BIRCH Sorting algorithm Merge algorithm CURE data clustering algorithm Data stream clustering
7	A Constraint-based Approach for Multispace Clustering Ruggero G. Pensa and Mirco Nanni Pisa KDD Laboratory, ISTI-CNR, IPisa, Italy {ruggero.pensa,mirco.nanni}@isti.cnr.it Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Cluster analysis Hierarchical clustering Network analysis Document clustering K-means clustering Constrained clustering Data stream clustering Consensus clustering
8	Scalable K-Means++ Bahman Bahmani Stanford University K-means Clustering   Fundamental problem in data analysis and machine learning Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-03-09 01:29:53 K-means++ K-means clustering Cluster analysis K-medians clustering Data stream clustering
9	Decision-theoretic Clustering of Strategies Add to Reading List Source URL: poker.cs.ualberta.ca Language: English - Date: 2015-03-04 17:02:48 Computational statistics Statistics Mathematics K-means clustering Hierarchical clustering Cluster analysis Image segmentation K-means++ Greedy algorithm K-medians clustering Data stream clustering Determining the number of clusters in a data set
10	PDF Document Add to Reading List Source URL: confsys.encs.concordia.ca Language: English - Date: 2016-02-13 15:52:58 Cluster analysis Statistics Data mining Geostatistics Geography of Portugal Consensus clustering Data analysis Constrained clustering Faculdade de Engenharia da Universidade do Porto Data stream clustering University of Porto Instituto Superior de Engenharia do Porto