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» A new approach to data driven clustering
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ML
2002
ACM
128views Machine Learning» more  ML 2002»
14 years 9 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
MLDM
2007
Springer
15 years 3 months ago
Kernel MDL to Determine the Number of Clusters
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...
Ivan O. Kyrgyzov, Olexiy O. Kyrgyzov, Henri Ma&ici...
IPMI
2009
Springer
15 years 10 months ago
Tractography Segmentation Using a Hierarchical Dirichlet Processes Mixture Model
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
ICDCS
2000
IEEE
15 years 2 months ago
An Adaptive, Perception-Driven Error Spreading Scheme in Continuous Media Streaming
For transmission of continuous media (CM) streams such as audio and video over the Internet, a critical issue is that periodic network overloads cause bursty packet losses. Studie...
Srivatsan Varadarajan, Hung Q. Ngo, Jaideep Srivas...
ICDM
2008
IEEE
115views Data Mining» more  ICDM 2008»
15 years 4 months ago
Toward Faster Nonnegative Matrix Factorization: A New Algorithm and Comparisons
Nonnegative Matrix Factorization (NMF) is a dimension reduction method that has been widely used for various tasks including text mining, pattern analysis, clustering, and cancer ...
Jingu Kim, Haesun Park