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» Comparing transformation methods for DNA microarray data
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DAGSTUHL
2009
15 years 3 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
127
Voted
ICIP
2008
IEEE
15 years 8 months ago
Video denoising using 3-D Hybrid Wavelets and Directional filter banks
We propose a new family of nonredundant 3-D directional transforms that are useful for video signals. In our construction, taking into account the correlation amongst frames of vi...
Ramin Eslami, Xiaolin Wu
157
Voted
BMCBI
2007
173views more  BMCBI 2007»
15 years 2 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 2 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan
125
Voted
ICMLA
2009
15 years 1 days ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara