What Machine Learning Tells Us About the Mathematical Structures of Concepts
“What are concepts?” is one of the fundamental questions in philosophy, where Aristotle, Kant, Wittgenstein, etc. have proposed different models of concepts. Meanwhile, machine learning literature has developed powerful methods to learn representation from data, as well as mathematical models to analyze such representations. This presentation aims to bridge these two traditions by identifying mathematical models & machine-learning counterparts of the (1) Aristotelian, (2) Wittgensteinian, (3) Functional, and (4) Symmetry-based theories of concept.