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The role of over-parametrization in generalization of neural networks

B. Neyshabur, Z. Li, S. Bhojanapalli, Y. LeCun, and N. Srebro. International Conference on Learning Representations, (2019)

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Coping with Label Shift via Distributionally Robust Optimisation.J. Zhang, A. Menon, A. Veit, S. Bhojanapalli, S. Kumar, and S. Sra. CoRR, (2020)A New Sampling Technique for Tensors.S. Bhojanapalli, and S. Sanghavi. CoRR, (2015)A Simple and Effective Positional Encoding for Transformers.P. Chen, H. Tsai, S. Bhojanapalli, H. Chung, Y. Chang, and C. Ferng. EMNLP (1), page 2974-2988. Association for Computational Linguistics, (2021)A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural NetworksB. Neyshabur, S. Bhojanapalli, and N. Srebro. (2017)cite arxiv:1707.09564Comment: Accepted to ICLR 2018.Dropping Convexity for Faster Semi-definite Optimization.S. Bhojanapalli, A. Kyrillidis, and S. Sanghavi. COLT, volume 49 of JMLR Workshop and Conference Proceedings, page 530-582. JMLR.org, (2016)Are Transformers universal approximators of sequence-to-sequence functions?C. Yun, S. Bhojanapalli, A. Rawat, S. Reddi, and S. Kumar. CoRR, (2019)The role of over-parametrization in generalization of neural networksB. Neyshabur, Z. Li, S. Bhojanapalli, Y. LeCun, and N. Srebro. International Conference on Learning Representations, (2019)Functional Interpolation for Relative Positions Improves Long Context Transformers.S. Li, C. You, G. Guruganesh, J. Ainslie, S. Ontañón, M. Zaheer, S. Sanghai, Y. Yang, S. Kumar, and S. Bhojanapalli. CoRR, (2023)Demystifying the Better Performance of Position Encoding Variants for Transformer.P. Chen, H. Tsai, S. Bhojanapalli, H. Chung, Y. Chang, and C. Ferng. CoRR, (2021)Understanding Robustness of Transformers for Image Classification.S. Bhojanapalli, A. Chakrabarti, D. Glasner, D. Li, T. Unterthiner, and A. Veit. ICCV, page 10211-10221. IEEE, (2021)

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The role of over-parametrization in generalization of neural networks

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML The role of over-parametrization in generalization of neural networks

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The role of over-parametrization in generalization of neural networks