Hands-On Meta Learning with Python

Content-based addressing

In content-based addressing, we select values from the memory based on similarity. The controller returns a key vector called . We compare this key vector, , with each of the rows in the memory matrix ,, to learn the similarity. We use cosine similarity as a similarity measure for checking the similarity, which can be expressed as follows:

We introduce a new parameter called , which is called the key strength. It determines ...