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Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions., , и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 4067-4077. PMLR, (2020)Towards theoretically-founded learning-based denoising., и . ISIT, стр. 2714-2718. IEEE, (2019)Compressibility and Generalization in Large-Scale Deep Learning, , , , и . (2018)cite arxiv:1804.05862Comment: 20 pages, 1 figure.Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach, , , , и . International Conference on Learning Representations, (2019)pmwd: A Differentiable Cosmological Particle-Mesh $N$-body Library, , , , , , , , , и . (2022)cite arxiv:2211.09958Comment: repo at https://github.com/eelregit/pmwd.Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data., , , , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 1733-1742. PMLR, (2019)Autobahn: Automorphism-based Graph Neural Nets., , и . NeurIPS, стр. 29922-29934. (2021)Discrete Object Generation with Reversible Inductive Construction., , , , и . NeurIPS, стр. 10353-10363. (2019)Vitruvion: A Generative Model of Parametric CAD Sketches., , , и . ICLR, OpenReview.net, (2022)Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions., , , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 5215-5224. PMLR, (2018)