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Are Transformers universal approximators of sequence-to-sequence functions?

C. Yun, S. Bhojanapalli, A. Rawat, S. Reddi, and S. Kumar. CoRR, (2019)

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A New Sampling Technique for Tensors.S. Bhojanapalli, and S. Sanghavi. CoRR, (2015)Coping with Label Shift via Distributionally Robust Optimisation.J. Zhang, A. Menon, A. Veit, S. Bhojanapalli, S. Kumar, and S. Sra. CoRR, (2020)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)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)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)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)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.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)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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Are Transformers universal approximators of sequence-to-sequence functions?

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Disambiguation of "Bhojanapalli, Srinadh"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Are Transformers universal approximators of sequence-to-sequence functions?

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Are Transformers universal approximators of sequence-to-sequence functions?