11 Matching Annotations
  1. Jan 2023
  2. Dec 2021
  3. Sep 2021
  4. Apr 2021
  5. Dec 2019
  6. Apr 2017
    1. Algorithmically, these models are similar, except that CBOW predicts target words (e.g. 'mat') from source context words ('the cat sits on the'), while the skip-gram does the inverse and predicts source context-words from the target words. This inversion might seem like an arbitrary choice, but statistically it has the effect that CBOW smoothes over a lot of the distributional information (by treating an entire context as one observation)