# Learners' languages

@article{Spivak2021LearnersL, title={Learners' languages}, author={David I. Spivak}, journal={ArXiv}, year={2021}, volume={abs/2103.01189} }

In “Backprop as functor”, the authors show that the fundamental elements of deep learning—gradient descent and backpropagation—can be conceptualized as a strong monoidal functor Para(Euc) → Learn from the category of parameterized Euclidean spaces to that of learners, a category developed explicitly to capture parameter update and backpropagation. It was soon realized that there is an isomorphism Learn Para(SLens), where SLens is the symmetric monoidal category of simple lenses as used in…

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