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» Classes and clusters in data analysis
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ICML
2007
IEEE
15 years 10 months ago
Adaptive dimension reduction using discriminant analysis and K-means clustering
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
Chris H. Q. Ding, Tao Li
CCGRID
2001
IEEE
15 years 1 months ago
TACO-Exploiting Cluster Networks for High-Level Collective Operations
TACO (Topologies and Collections) is a template library that introduces the flavour of distributed data parallel processing by means of reusable topology classes and C++ s. This p...
Jörg Nolte, Mitsuhisa Sato, Yutaka Ishikawa
IJCNN
2000
IEEE
15 years 2 months ago
EM Algorithms for Self-Organizing Maps
eresting web-available abstracts and papers on clustering: An Analysis of Recent Work on Clustering Algorithms (1999), Daniel Fasulo : This paper describes four recent papers on cl...
Tom Heskes, Jan-Joost Spanjers, Wim Wiegerinck
CORR
1999
Springer
222views Education» more  CORR 1999»
14 years 9 months ago
Analysis of approximate nearest neighbor searching with clustered point sets
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
Songrit Maneewongvatana, David M. Mount
DIS
2006
Springer
15 years 1 months ago
On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets
Parametric Embedding (PE) has recently been proposed as a general-purpose algorithm for class visualisation. It takes class posteriors produced by a mixture-based clustering algori...
Ata Kabán, Jianyong Sun, Somak Raychaudhury...