Jointly learning relevant subgraph patterns and nonlinear models of their indicators

@article{Shirakawa2018JointlyLR,
  title={Jointly learning relevant subgraph patterns and nonlinear models of their indicators},
  author={Ryo Shirakawa and Yusei Yokoyama and Fumiya Okazaki and Ichigaku Takigawa},
  journal={CoRR},
  year={2018},
  volume={abs/1807.02963}
}
Classification and regression in which the inputs are graphs of arbitrary size and shape have been paid attention in various fields such as computational chemistry and bioinformatics. Subgraph indicators are often used as the most fundamental features, but the number of possible subgraph patterns are intractably large due to the combinatorial explosion. We… CONTINUE READING