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» Spectral Clustering with Perturbed Data
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BMCBI
2007
171views more  BMCBI 2007»
13 years 7 months ago
Classification of microarray data using gene networks
Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) a...
Franck Rapaport, Andrei Zinovyev, Marie Dutreix, E...
BMCBI
2010
89views more  BMCBI 2010»
13 years 7 months ago
Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS)
Background: Nuclear magnetic resonance spectroscopy is one of the primary tools in metabolomics analyses, where it is used to track and quantify changes in metabolite concentratio...
Jennifer M. Staab, Thomas M. O'Connell, Shawn M. G...
DAGM
2011
Springer
12 years 7 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
FIMH
2009
Springer
14 years 2 months ago
Cardiac Fibre Trace Clustering for the Interpretation of the Human Heart Architecture
Cardiac fibre architecture plays a key role in heart function. Recently, the estimation of fibre structure has been simplified with diffusion tensor MRI (DT-MRI). In order to as...
Carole Frindel, Marc C. Robini, Joël Schaerer...
ML
2010
ACM
127views Machine Learning» more  ML 2010»
13 years 6 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby