Sparse distributed memory is a continual learner

TitleSparse distributed memory is a continual learner
Publication TypeConference Poster
Year of Publication2023
AuthorsBricken, T, Davies, X, Singh, D, Krotov, D, Kreiman, G
Conference NameInternational Conference on Learning Representations
Date Published03/2023
Place PublishedKigali, Rwanda, Africa
KeywordsBiologically Inspired, Continual Learning, Sparse Distributed Memory, Sparsity, Top-K Activation

Continual learning is a problem for artificial neural networks that their biological counterparts are adept at solving. Building on work using Sparse Distributed Memory (SDM) to connect a core neural circuit with the powerful Transformer model, we create a modified Multi-Layered Perceptron (MLP) that is a strong continual learner. We find that every component of our MLP variant translated from biology is necessary for continual learning. Our solution is also free from any memory replay or task information, and introduces novel methods to train sparse networks that may be broadly applicable.

Citation Key5254

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