In this paper, we revisit implicit regularization from the ground up using notions from dynamical systems and invariant subspaces of Morse functions. The key contributions are a new criterion for implicit regularizationa leading contender to explain the generalization power of deep models such as neural networksand a general blueprint to study it. We apply these techniques to settle a conjecture on implicit regularization in matrix factorization.
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