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TVLSI
2010
9 years 6 months ago
Bandwidth Adaptive Hardware Architecture of K-Means Clustering for Video Analysis
K-Means is a clustering algorithm that is widely applied in many fields, including pattern classification and multimedia analysis. Due to real-time requirements and computational-c...
Tse-Wei Chen, Shao-Yi Chien
MLDM
2010
Springer
9 years 6 months ago
Fast Algorithms for Constant Approximation k-Means Clustering
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...
Mingjun Song, Sanguthevar Rajasekaran
CLASSIFICATION
2010
9 years 9 months ago
Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads
: The issue of determining "the right number of clusters" in K-Means has attracted considerable interest, especially in the recent years. Cluster intermix appears to be a...
Mark Ming-Tso Chiang, Boris Mirkin
ICASSP
2011
IEEE
9 years 9 months ago
Non-flat clustering whith alpha-divergences
The scope of the well-known k-means algorithm has been broadly extended with some recent results: first, the k- means++ initialization method gives some approximation guarantees...
Olivier Schwander, Frank Nielsen
ICONIP
2009
9 years 9 months ago
Text Mining with an Augmented Version of the Bisecting K-Means Algorithm
There is an ever increasing number of electronic documents available today and the task of organizing and categorizing this ever growing corpus of electronic documents has become t...
Yutaro Hatagami, Toshihiko Matsuka
ICANNGA
2009
Springer
173views Algorithms» more  ICANNGA 2009»
9 years 9 months ago
On Document Classification with Self-Organising Maps
Abstract This research deals with the use of self-organising maps for the classification of text documents. The aim was to classify documents to separate classes according to their...
Jyri Saarikoski, Kalervo Järvelin, Jorma Laur...
ICPR
2010
IEEE
9 years 9 months ago
On Dynamic Weighting of Data in Clustering with K-Alpha Means
Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a...
Sibao Chen, Haixian Wang, Bin Luo
ICIP
2010
IEEE
9 years 9 months ago
Edge-adaptive image segmentation based on seam processing and K-Means clustering
A new image segmentation method is proposed to combine the edge information with the feature-space method, K-Means clustering. A procedure called seam processing, which is computa...
Tse-Wei Chen, Hsiao-Hang Su, Yi-Ling Chen, Shao-Yi...
FOCS
2010
IEEE
9 years 9 months ago
Stability Yields a PTAS for k-Median and k-Means Clustering
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...
Pranjal Awasthi, Avrim Blum, Or Sheffet
PRL
2007
150views more  PRL 2007»
9 years 11 months ago
A method for initialising the K-means clustering algorithm using kd-trees
We present a method for initialising the K-means clustering algorithm. Our method hinges on the use of a kd-tree to perform a density estimation of the data at various locations. ...
Stephen J. Redmond, Conor Heneghan
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