Towards Initialization-dependent and Non-vacuous Generalization Bounds for Overparameterized Shallow Neural Networks
Towards Initialization-dependent and Non-vacuous Generalization Bounds for Overparameterized Shallow Neural Networks explores Develops fully initialization-dependent complexity bounds for shallow neural networks with general Lipschitz activation functions, offering non-vacuous generalization bounds for overparameterized models. in Machine Learning Theory.
Updated 23 hours ago
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