Data Science Asked by Selma_KA on January 13, 2021
In many research papers there are ‘projection layers’ related to BLSTM layers. For example, from here:
"we trained an 8-layer BLSTM encoder including 320 cells in each layer
and direction, and the linear projection layer with 320 units followed
by each BLSTM layer"
I can’t understand what this means and how it works.
Any help on this topic would be appreciated. Thanks in advance!
A "projection" is a simple linear/dense layer, that is, a matrix multiplication and a bias vector addition.
It is called projection because you "project" a representation of dimensionality $M$ into a representation space of dimensionality $N$.
Sometimes, especially for sequences or 2D data, these projections are implemented as a convolution of size 1, which is equivalent to the computations I described above.
Correct answer by ncasas on January 13, 2021
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