Memory in machine learning

March 3, 2021 — March 3, 2021

language
machine learning
neural nets
NLP
Figure 1

How best should learning algorithms store and retrieve memories? Important in reinforcement learning. Implicit in recurrent networks. One of the chief advantages of neural Turing machines. A great apparent success of transformers is that they have an idea of what to remember backed in to their context window. As my colleague Tom Blau points out, perhaps best considered as a topic in its own right. Is it distinct from continual learning?

1 References

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Graves, Wayne, Reynolds, et al. 2016. “Hybrid Computing Using a Neural Network with Dynamic External Memory.” Nature.
Grefenstette, Hermann, Suleyman, et al. 2015. “Learning to Transduce with Unbounded Memory.” arXiv:1506.02516 [Cs].
Hochreiter, and Schmidhuber. 1997. “Long Short-Term Memory.” Neural Computation.
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