A hierarchy of meta-learners, each generating virtual tasks for the level below, is proposed as a category-theoretic framework for recursive higher-order meta-learning.
A general framework for equivariant neural networks on reductive lie groups
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High-Order Deep Meta-Learning with Category-Theoretic Interpretation
A hierarchy of meta-learners, each generating virtual tasks for the level below, is proposed as a category-theoretic framework for recursive higher-order meta-learning.