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Clustering
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#	Item
351	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++
352	Discussion of “Spectral Dimensionality Reduction via Maximum Entropy” Laurens van der Maaten Delft University of Technology Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Multivariate statistics Dimension reduction Computational statistics Machine learning Dimension Nonlinear dimensionality reduction Dimensionality reduction Isomap Semidefinite embedding Spectral clustering Kernel principal component analysis T-distributed stochastic neighbor embedding
353	Metric Clustering via Consistent Labeling Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2010-09-28 14:30:42 Combinatorial optimization Operations research NP-complete problems Approximation algorithms Computational problems Linear programming Minimum k-cut Optimization problem Ear decomposition Decomposition method
354	Proceedings Template - WORD Add to Reading List Source URL: www.geovista.psu.edu Language: English - Date: 2016-07-01 14:44:37 Network theory Social networks Self-organization Social information processing Systems theory Information visualization Graph drawing JUNG Spatial analysis Social network analysis Clustering coefficient Core-periphery structure
355	Candidacy Exam Progressive Classification of Images and Videos on the World Wide Web Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Data mining Machine learning Cluster analysis Geostatistics Statistical classification Hierarchical clustering
356	Microsoft PowerPoint - GeocompCluster.ppt Add to Reading List Source URL: www.iam.fmph.uniba.sk Language: English - Date: 2012-03-20 04:55:55 Means Cluster analysis K-means clustering Hierarchical clustering Medoid K-medoids Centroid Determining the number of clusters in a data set K-medians clustering
357	An Interactive Visual Testbed System for Dimension Reduction and Clustering of Large-scale High-dimensional Data Jaegul Choo, Hanseung Lee, Zhicheng Liu, John Stasko, and Haesun Park Georgia Institute of Technology, USA Add to Reading List Source URL: www.zcliu.org Language: English - Date: 2016-07-30 20:21:03 Visualization Multivariate statistics Dimension reduction Data Data visualization Information technology governance K-means clustering Parallel coordinates Principal component analysis Information visualization Spectral clustering Data analysis
358	EE103, FallS. Boyd Homework 3 1. Linear combinations of cash flows. We consider cash flow vectors over T time periods, Add to Reading List Source URL: stanford.edu Language: English - Date: 2015-10-17 01:19:24 Vector calculus Linear algebra Abstract algebra Euclidean vector Vectors Centroid K-means clustering Vandermonde matrix Matrix
359	Visually and Acoustically Exploring the High-Dimensional Space of Music Lukas Bossard Computer Engineering and Networks Laboratory ETH Zurich, Switzerland Add to Reading List Source URL: disco.ethz.ch Language: English - Date: 2014-09-26 08:36:25 Visualization Discrete geometry Virtual reality Computational geometry Diagrams Voronoi diagram K-means clustering Recommender system User interface Self-organizing map Hierarchical clustering VisIt
360	Optical Flow Clustering for ROI Coding ¨ Ostermann Holger Meuel · Marco Munderloh · Matthias Reso · Jorn Problem and Goal Goal: Transmission of HDTV video over narrow bandwidth channels Add to Reading List Source URL: www.tnt.uni-hannover.de Language: English - Date: 2014-10-14 04:30:07 Video compression Motion compensation Motion estimation Optical flow Motion detection Image segmentation Conference on Computer Vision and Pattern Recognition Motion vector High-definition television

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