- They use more parameters (and fewer computations per parameter.)
- They are hierarchical (convolutions are apparently useful at different levels of abstraction of data).
- They are distributed (word2vec, thought-vectors). Not restricted to a small set of artificial classes such as parts-of-speech or parts of visual objects.
Comments
They are effective because:
- They use more parameters (and fewer computations per parameter.)
- They are hierarchical (convolutions are apparently useful at different levels of abstraction of data).
- They are distributed (word2vec, thought-vectors). Not restricted to a small set of artificial classes such as parts-of-speech or parts of visual objects.
- They are recurrent (RNN).
etc.
word2vec isn't "deep" in the relevant sense. The both skipgram and CBOW forms have a single hidden layer.