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CVPR
2010
IEEE
14 years 6 months ago
Sufficient Dimensionality Reduction for Visual Sequence Classification
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
Alex Shyr, Raquel Urtasun, Michael Jordan
ICASSP
2009
IEEE
14 years 4 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
NN
2006
Springer
153views Neural Networks» more  NN 2006»
13 years 10 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
ESANN
2006
13 years 11 months ago
Using distributed genetic programming to evolve classifiers for a brain computer interface
The objective of this paper is to illustrate the application of genetic programming to evolve classifiers for multi-channel time series data. The paper shows how high performance d...
Eva Alfaro-Cid, Anna Esparcia-Alcázar, Ken ...
CLASSIFICATION
2008
84views more  CLASSIFICATION 2008»
13 years 10 months ago
Degenerating Families of Dendrograms
Dendrograms used in data analysis are ultrametric spaces, hence objects of nonarchimedean geometry. It is known that there exist p-adic representations of dendrograms. Completed b...
Patrick Erik Bradley