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PAKDD
2005
ACM
112views Data Mining» more  PAKDD 2005»
15 years 12 months ago
Approximated Clustering of Distributed High-Dimensional Data
In many modern application ranges high-dimensional feature vectors are used to model complex real-world objects. Often these objects reside on different local sites. In this paper,...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...
ESEM
2007
ACM
15 years 8 months ago
An Approach to Outlier Detection of Software Measurement Data using the K-means Clustering Method
The quality of software measurement data affects the accuracy of project manager’s decision making using estimation or prediction models and the understanding of real project st...
Kyung-A Yoon, Oh-Sung Kwon, Doo-Hwan Bae
CVPR
2007
IEEE
16 years 8 months ago
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
A popular approach to problems in image classification is to represent the image as a bag of visual words and then employ a classifier to categorize the image. Unfortunately, a si...
Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukt...
ICML
2007
IEEE
16 years 7 months ago
Cluster analysis of heterogeneous rank data
Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Emp...
Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann
RECOMB
2001
Springer
16 years 6 months ago
Context-specific Bayesian clustering for gene expression data
The recent growth in genomic data and measurements of genome-wide expression patterns allows us to apply computational tools to examine gene regulation by transcription factors. I...
Yoseph Barash, Nir Friedman