Translations:Word Embeddings/24/en: Difference between revisions
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Latest revision as of 23:34, 27 April 2026
- Negative sampling — instead of computing the full softmax, the model contrasts the true context word against $ k $ randomly sampled "negative" words.
- Hierarchical softmax — organises the vocabulary in a binary tree, reducing the softmax cost from $ O(V) $ to $ O(\log V) $.