Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
ICML, pp. 1665-1674, 2017.
We consider multi-class classification where the predictor has a hierarchical structure that allows for a very large number of labels both at train and test time. The predictive power of such models can heavily depend on the structure of the tree, and although past work showed how to learn the tree structure, it expected that the feature ...More
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