Hypergraph regularized sparse feature learning

@article{Liu2017HypergraphRS,
  title={Hypergraph regularized sparse feature learning},
  author={Mingxia Liu and Jun Zhang and Xiaochun Guo and Liujuan Cao},
  journal={Neurocomputing},
  year={2017},
  volume={237},
  pages={185-192}
}
As an important pre-processing stage in many machine learning and pattern recognition domains, feature selection deems to identify the most discriminate features for a compact data representation. As typical feature selection methods, Lasso and its variants using the l1-norm based regularization have received much attention in recent years. However, most of existing l1-norm based sparse feature selection methods ignore the structure information of data or only consider the pairwise… CONTINUE READING
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Statistical Learning with Sparsity: The 350 Lasso and Generalizations

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Highly Influential
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