title: Why word2vec doesn't use regularization?
body: <p>ML models with huge number of parameters will tend to overfit (since they have a large variance). In my opinion, <code>word2vec</code> is one such models. One of the ways to reduce the model variance is to apply a regularization technique, which is very common thing for the other embedding models, such as matrix factorization. However, the basic version of <code>word2vec</code> doesn't have any regularization part. Is there a reason for this?</p>