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» REDUS: finding reducible subspaces in high dimensional data
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KDD
2001
ACM
169views Data Mining» more  KDD 2001»
14 years 8 months ago
Hierarchical cluster analysis of SAGE data for cancer profiling
In this paper we present a method for clustering SAGE (Serial Analysis of Gene Expression) data to detect similarities and dissimilarities between different types of cancer on the...
Jörg Sander, Monica C. Sleumer, Raymond T. Ng
ICML
2005
IEEE
14 years 8 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
NIPS
2001
13 years 9 months ago
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
Nicolas Chapados, Yoshua Bengio, Pascal Vincent, J...
IEEEMM
2007
146views more  IEEEMM 2007»
13 years 7 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
KDD
2005
ACM
178views Data Mining» more  KDD 2005»
14 years 1 months ago
Failure detection and localization in component based systems by online tracking
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...