Papers by Miguel A. Carreira-Perpinan
Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large (2021.emnlp-main)
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| Challenge: | Classification problems with thousands or more classes occur in NLP, for example language models or document classification. |
| Approach: | a new algorithm uses a binary tree with sparse hyperplanes and small softmax classifiers at the leaves to predict the top class. |
| Outcome: | The proposed model is faster at inference because the input follows a single path to a leaf and the softmax classifier operates on a small subset of the classes. |