• Corpus ID: 146121288

Characterizing the invariances of learning algorithms using category theory

  title={Characterizing the invariances of learning algorithms using category theory},
  author={Kenneth D. Harris},
  • K. Harris
  • Published 6 May 2019
  • Mathematics, Computer Science
  • ArXiv
Many learning algorithms have invariances: when their training data is transformed in certain ways, the function they learn transforms in a predictable manner. Here we formalize this notion using concepts from the mathematical field of category theory. The invariances that a supervised learning algorithm possesses are formalized by categories of predictor and target spaces, whose morphisms represent the algorithm's invariances, and an index category whose morphisms represent permutations of the… 
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