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Auto-encoders: reconstruction versus compression.. CoRR, (2014)Learning with Random Learning Rates., , и . ECML/PKDD (2), том 11907 из Lecture Notes in Computer Science, стр. 449-464. Springer, (2019)Interpreting a Penalty as the Influence of a Bayesian Prior., , и . CoRR, (2020)Do Deep Learning Models Have Too Many Parameters? An Information Theory Viewpoint., и . CoRR, (2018)First-Order Adversarial Vulnerability of Neural Networks and Input Dimension., , , , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 5809-5817. PMLR, (2019)Making Deep Q-learning methods robust to time discretization., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 6096-6104. PMLR, (2019)Laplace's Rule of Succession in Information Geometry.. GSI, том 9389 из Lecture Notes in Computer Science, стр. 311-319. Springer, (2015)Learning One Representation to Optimize All Rewards., и . NeurIPS, стр. 13-23. (2021)White-box vs Black-box: Bayes Optimal Strategies for Membership Inference., , , , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 5558-5567. PMLR, (2019)Can recurrent neural networks warp time?, и . ICLR (Poster), OpenReview.net, (2018)