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Empirical Analysis of the Hessian of Over-Parametrized Neural Networks., , , , and . CoRR, (2017)Empirical Analysis of the Hessian of Over-Parametrized Neural Networks, , , , and . (2017)cite arxiv:1706.04454Comment: Minor update for ICLR 2018 Workshop Track presentation.Triple descent and the two kinds of overfitting: where & why do they appear?, , and . NeurIPS, (2020)Confusing Large Models by Confusing Small Models., , , , , and . ICCV (Workshops), page 4306-4314. IEEE, (2023)ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases., , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 2286-2296. PMLR, (2021)A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks, , and . (2019)cite arxiv:1901.06053.Easing non-convex optimization with neural networks., and . ICLR (Workshop), OpenReview.net, (2018)Measuring and signing fairness as performance under multiple stakeholder distributions., , , and . CoRR, (2022)Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond, , and . arXiv preprint arXiv:1611.07476, (2016)On the interplay between data structure and loss function in classification problems., , , and . NeurIPS, page 8506-8517. (2021)