Efficient locality weighted sparse representation for graph-based learning

@article{Feng2017EfficientLW,
  title={Efficient locality weighted sparse representation for graph-based learning},
  author={Xiaodong Feng and Sen Wu and Wenjun Zhou and Min Quan},
  journal={Knowl.-Based Syst.},
  year={2017},
  volume={121},
  pages={129-141}
}
Constructing a graph to represent the structure among data objects plays a fundamental role in various data mining tasks with graph-based learning. Since traditional pairwise distance-based graph construction is sensitive to noise and outliers, sparse representation based graphs (e.g., 1 -graphs) have been proposed in the literature. Although 1 -graphs prove powerful and robust for many graph-based learning tasks, it suffers from weak locality and high computation costs. In this paper, we… CONTINUE READING
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