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» Learning from Highly Structured Data by Decomposition
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ICDM
2008
IEEE
155views Data Mining» more  ICDM 2008»
15 years 10 months ago
Organic Pie Charts
We present a new visualization of the distance and cluster structure of high dimensional data. It is particularly well suited for analysis tasks of users unfamiliar with complex d...
Fabian Mörchen
ISMB
1996
15 years 5 months ago
A Knowledge-Based Method for Protein Structure Refinement and Prediction
The native conformation of a protein, in a given environment, is determined entirely by the various interatomic interactions dictated by the amino acid sequence (1-3). We describe...
Shankar Subramaniam, David K. Tcheng, James M. Fen...
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 4 months ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
ACCV
2006
Springer
15 years 6 months ago
Learning Multi-category Classification in Bayesian Framework
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Atul Kanaujia, Dimitris N. Metaxas
ICML
2005
IEEE
16 years 5 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane