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Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization

, , and . (2019)cite arxiv:1908.09375Comment: arXiv admin note: text overlap with arXiv:1611.00740.

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Theory IIIb: Generalization in Deep Networks., , , , , and . CoRR, (2018)Double descent in the condition number., , and . CoRR, (2019)Biologically Inspired Mechanisms for Adversarial Robustness., , , and . NeurIPS, (2020)A Surprising Linear Relationship Predicts Test Performance in Deep Networks., , , , and . CoRR, (2018)Theory III: Dynamics and Generalization in Deep Networks., , , , , , and . CoRR, (2019)Distribution of Classification Margins: Are All Data Equal?, , , , and . CoRR, (2021)Cross-Domain Adversarial Reprogramming of a Recurrent Neural Network., , and . CogSci, cognitivesciencesociety.org, (2020)Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization, , and . (2019)cite arxiv:1908.09375Comment: arXiv admin note: text overlap with arXiv:1611.00740.Neural-Guided, Bidirectional Program Search for Abstraction and Reasoning., , , , , , , , and . COMPLEX NETWORKS, volume 1015 of Studies in Computational Intelligence, page 657-668. Springer, (2021)The RealityMashers: Augmented Reality Wide Field-of-View Optical See-Through Head Mounted Displays., , , , , , , , , and 4 other author(s). ISMAR Adjunct, page 141-146. IEEE Computer Society, (2016)