154 citations · 359 across the 22 of their papers we have counts for
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cs.LG2019★ 39 cited
Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian
Samet Oymak, Zalan Fabian, Mingchen Li +1
Modern neural network architectures often generalize well despite containing many more parameters than the size of the training dataset. This paper explores the generalization capa…
cs.LG2019★ 154 cited
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak
Modern neural networks are typically trained in an over-parameterized regime where the parameters of the model far exceed the size of the training data. Such neural networks in pri…