Distributed vs. Distributional Representations

Distributed Representations = Learnt using Deep Learning methods. Distributed over the parameter space. Dense, lower dimensional embeddings.

Distributional Representations = Counted from a corpus. Classical distributional hypothesis. Sparse, High dimensional.