<--- Back to Details
First PageDocument Content
Machine learning / K-means clustering / K-medians clustering / Cluster analysis / Fisher–Yates shuffle / Data stream clustering / Consensus clustering / Statistics / Computational statistics / K-means++
Date: 2012-02-28 09:44:55
Machine learning
K-means clustering
K-medians clustering
Cluster analysis
Fisher–Yates shuffle
Data stream clustering
Consensus clustering
Statistics
Computational statistics
K-means++

Scalable K-Means++ Bahman Bahmani∗† Benjamin Moseley∗‡ Andrea Vattani∗§

Add to Reading List

Source URL: theory.stanford.edu

Download Document from Source Website

File Size: 374,08 KB

Share Document on Facebook

Similar Documents

Data mining / Statistics / Computational statistics / Software / Machine learning / Massive Online Analysis / Cluster analysis / Formal sciences / Data stream mining / K-means clustering / Concept drift / Weka

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

DocID: 1rlVr - View Document

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

Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner

DocID: 1riQ6 - View Document

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

CS264: Beyond Worst-Case Analysis Lecture #6: Clustering in Approximation-Stable Instances∗ Tim Roughgarden† October 10, 2014

DocID: 1q8qV - View Document

Cluster analysis / Image segmentation / Statistics / Computational statistics / Data analysis / Data stream clustering

Ulaş Ayaz ICERM, Brown University Subspace Clustering with Ordered Weighted L1 Minimization

DocID: 1pQAo - View Document

Cluster analysis / Consensus clustering / Correlation clustering / K-means clustering / Data stream clustering / K-means++

Clustering Aggregation ARISTIDES GIONIS Yahoo! Research Labs, Barcelona HEIKKI MANNILA University of Helsinki and Helsinki University of Technology and

DocID: 1pGvp - View Document