A synthesis of approximation, optimization, and generalization theory arguing that gradient descent's implicit norm control on weight directions explains why overparameterized deep networks generalize.
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Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization
A synthesis of approximation, optimization, and generalization theory arguing that gradient descent's implicit norm control on weight directions explains why overparameterized deep networks generalize.