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On the interplay between noise and curvature and its effect on optimization and generalization.

, , , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3503-3513. PMLR, (2020)

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Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples., , , , , , , , , and 1 other author(s). ICLR, OpenReview.net, (2020)Extracting and composing robust features with denoising autoencoders., , , and . ICML, volume 307 of ACM International Conference Proceeding Series, page 1096-1103. ACM, (2008)On the interplay between noise and curvature and its effect on optimization and generalization., , , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3503-3513. PMLR, (2020)Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples., , , , , , , , , and . CoRR, (2019)Why Does Unsupervised Pre-training Help Deep Learning?, , , , , and . J. Mach. Learn. Res., (2010)Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion., , , , and . J. Mach. Learn. Res., (2010)Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples, , , , , , , , , and 1 other author(s). (2019)cite arxiv:1903.03096Comment: Code available at https://github.com/google-research/meta-dataset.Online variance-reducing optimization., , and . ICLR (Workshop), OpenReview.net, (2018)Reducing the variance in online optimization by transporting past gradients., , , , and . NeurIPS, page 5392-5403. (2019)Negative eigenvalues of the Hessian in deep neural networks., , and . CoRR, (2019)