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ICMLA
2009
13 years 5 months ago
2009
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
WER
2010
Springer
13 years 5 months ago
2010
Springer
Feature models are commonly used to capture the commonality and the variability of product families. There are several feature model notations that correspondingly depict the conce...
TCSV
2010
13 years 2 months ago
2010
In this letter, we propose a clustering model that efficiently mitigates image and video under/over-segmentation by combining generalized Gaussian mixture modeling and feature sele...
PPSN
2010
Springer
13 years 5 months ago
2010
Springer
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
JMLR
2010
13 years 2 months ago
2010
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...