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» A dependence maximization view of clustering
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ICML
2007
IEEE
14 years 5 months ago
A dependence maximization view of clustering
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
Le Song, Alexander J. Smola, Arthur Gretton, Karst...
KDD
2010
ACM
279views Data Mining» more  KDD 2010»
13 years 8 months ago
Unifying dependent clustering and disparate clustering for non-homogeneous data
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
NIPS
2008
13 years 5 months ago
Learning Taxonomies by Dependence Maximization
We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
Matthew B. Blaschko, Arthur Gretton
MIR
2010
ACM
188views Multimedia» more  MIR 2010»
13 years 4 months ago
Beyond 2D-grids: a dependence maximization view on image browsing
Ideally, one would like to perform image search using an intuitive and friendly approach. Many existing image search engines, however, present users with sets of images arranged i...
Novi Quadrianto, Kristian Kersting, Tinne Tuytelaa...
VIS
2004
IEEE
166views Visualization» more  VIS 2004»
14 years 5 months ago
Quick-VDR: Interactive View-Dependent Rendering of Massive Models
We present a novel approach for interactive view-dependent rendering of massive models. Our algorithm combines view-dependent simplification, occlusion culling, and out-of-core re...
Sung-Eui Yoon, Brian Salomon, Russell Gayle, Dines...