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» Accelerated EM-based clustering of large data sets
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WG
2010
Springer
13 years 6 months ago
Generalized Graph Clustering: Recognizing (p, q)-Cluster Graphs
Cluster Editing is a classical graph theoretic approach to tackle the problem of data set clustering: it consists of modifying a similarity graph into a disjoint union of cliques,...
Pinar Heggernes, Daniel Lokshtanov, Jesper Nederlo...
TSP
2008
167views more  TSP 2008»
13 years 6 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
VLUDS
2010
184views Visualization» more  VLUDS 2010»
13 years 2 months ago
Advanced Visualization and Interaction Techniques for Large High-Resolution Displays
Large high-resolution displays combine the images of multiple smaller display devices to form one large display area. A total resolution that can easily comprise several hundred m...
Sebastian Thelen
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
14 years 1 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
ESORICS
2005
Springer
14 years 1 months ago
Privacy Preserving Clustering
The freedom and transparency of information flow on the Internet has heightened concerns of privacy. Given a set of data items, clustering algorithms group similar items together...
Somesh Jha, Louis Kruger, Patrick McDaniel