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» Approximation algorithms for projective clustering
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107
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MP
2006
137views more  MP 2006»
15 years 17 days ago
New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
Yu-Hong Dai, Roger Fletcher
119
Voted
DEXAW
2010
IEEE
204views Database» more  DEXAW 2010»
15 years 1 months ago
Scalable Recursive Top-Down Hierarchical Clustering Approach with Implicit Model Selection for Textual Data Sets
Automatic generation of taxonomies can be useful for a wide area of applications. In our application scenario a topical hierarchy should be constructed reasonably fast from a large...
Markus Muhr, Vedran Sabol, Michael Granitzer
DIS
2006
Springer
15 years 4 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...
109
Voted
SIAMNUM
2010
103views more  SIAMNUM 2010»
14 years 7 months ago
Hybridization and Postprocessing Techniques for Mixed Eigenfunctions
Abstract. We introduce hybridization and postprocessing techniques for the RaviartThomas approximation of second-order elliptic eigenvalue problems. Hybridization reduces the Ravia...
Bernardo Cockburn, Jayadeep Gopalakrishnan, F. Li,...
140
Voted
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
16 years 1 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle