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AUSDM
2008
Springer
238views Data Mining» more  AUSDM 2008»
13 years 11 months ago
Graphics Hardware based Efficient and Scalable Fuzzy C-Means Clustering
The exceptional growth of graphics hardware in programmability and data processing speed in the past few years has fuelled extensive research in using it for general purpose compu...
S. A. Arul Shalom, Manoranjan Dash, Minh Tue
CICLING
2009
Springer
14 years 9 months ago
Improved Unsupervised Name Discrimination with Very Wide Bigrams and Automatic Cluster Stopping
We cast name discrimination as a problem in clustering short contexts. Each occurrence of an ambiguous name is treated independently, and represented using second?order context vec...
Ted Pedersen
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
13 years 9 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
BMVC
2001
13 years 11 months ago
An EM-like Algorithm for Motion Segmentation via Eigendecomposition
This paper presents an iterative maximum likelihood framework for motion segmentation via the pairwise checking of pixel blocks. We commence from a characterisation of the motion ...
Antonio Robles-Kelly, Edwin R. Hancock
ICASSP
2010
IEEE
13 years 9 months ago
Distributed Lasso for in-network linear regression
The least-absolute shrinkage and selection operator (Lasso) is a popular tool for joint estimation and continuous variable selection, especially well-suited for the under-determin...
Juan Andrés Bazerque, Gonzalo Mateos, Georg...