Review for NeurIPS paper: Coherent Hierarchical Multi-Label Classification Networks

Additional Feedback: I liked the toy examples, which illustrate in which situations the algorithm might work well. I would argue that the setting where a child label corresponds to a region of the space that is fully included by the bigger region of its parent label is most logical. For hierarchical multi-label classification problems, child labels can often semantically be seen as specializations of their parent labels. This can indeed be translated to the feature space, but I would argue that in practice this happens in a slightly different way. Child labels often have the same features active as their parents, e.g.