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BMCBI
2010
139views more  BMCBI 2010»
15 years 6 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
BMCBI
2010
151views more  BMCBI 2010»
15 years 6 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 6 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
CVPR
2007
IEEE
16 years 2 days ago
Estimating Cluster Overlap on Manifolds and its Application to Neuropsychiatric Disorders
Although it is usually assumed in many pattern recognition problems that different patterns are distinguishable, some patterns may have inseparable overlap. For example, some faci...
Peng Wang, Christian Köhler, Ragini Verma
EUROMICRO
2000
IEEE
15 years 10 months ago
Efficient Image Compression of Medical Images Using the Wavelet Transform and Fuzzy c-means Clustering on Regions of Interest
This paper suggests a novel image compression scheme, using the discrete wavelet transformation (DWT) and the fuzzy c-means clustering technique. The goal is to achieve higher com...
Dimitris A. Karras, S. A. Karkanis, Dimitrios E. M...