468 search results - page 13 / 94 » Optimization of in-network data reduction |
ML
2010
ACM
14 years 8 months ago
2010
ACM
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
87
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CVPR
2010
IEEE
15 years 5 months ago
2010
IEEE
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...
164
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ICDE
2008
IEEE
15 years 11 months ago
2008
IEEE
Despite the surge of interest in data reduction techniques over the past years, no method has been proposed to date that can always achieve approximation quality preferable to that...
FUIN
2002
14 years 9 months ago
2002
We use information entropy measure to extend the rough set based notion of a reduct. We introduce the Approximate Entropy Reduction Principle (AERP). It states that any simplificat...
100
Voted
ICIC
2005
Springer
15 years 3 months ago
2005
Springer
Dimension reduction is a crucial step for pattern recognition and information retrieval tasks to overcome the curse of dimensionality. In this paper a novel unsupervised linear dim...