Reviews: Label Distribution Learning Forests

The authors describe a method for label distribution learning based on differentiable decision trees. The authors use differentiable sigmoid units to estimate a label distribution using leaf nodes of trees. Learning in split nodes is done via backprop. The authors compare their work with relevant methods on learning label distributions and show the competitiveness of their method. I think this is a good paper, providing a sound methodology for learning LD.