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arXiv: 2212.01572

Zhang, Y., &; Vatedka, S. (2023). Multiple packing: Lower bounds via error exponents. IEEE Transactions on Information Theory. IEEE.https://doi.org/10.1109/TIT.2023.3334032 
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Zhang, Y. (2023). Zero-error communication over adversarial MACs. IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/tit.2023.3257239 
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Polyanskii, N., &; Zhang, Y. (2023). Codes for the Z-channel. IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/TIT.2023.3292219 
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Bombari, S., Kiyani, S., &; Mondelli, M. (2023). Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 2738–2776). Honolulu, HI, United States: ML Research Press.
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Súkeník, P., Mondelli, M., &; Lampert, C. (n.d.). Deep neural collapse is provably optimal for the deep unconstrained features model. In 37th Annual Conference on Neural Information Processing Systems. New Orleans, LA, United States.
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Wu, D., Kungurtsev, V., &; Mondelli, M. (2023). Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. In Transactions on Machine Learning Research. ML Research Press.
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arXiv: 2210.06819

Fu, T., Liu, Y., Barbier, J., Mondelli, M., Liang, S., &; Hou, T. (n.d.). Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. In Proceedings of 2023 IEEE International Symposium on Information Theory. Taipei, Taiwan: IEEE.https://doi.org/10.1109/isit54713.2023.10206671 
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arXiv: 2302.03306

Esposito, A. R., &; Mondelli, M. (2023). Concentration without independence via information measures. In Proceedings of 2023 IEEE International Symposium on Information Theory (pp. 400–405). Taipei, Taiwan: IEEE.https://doi.org/10.1109/isit54713.2023.10206899 
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arXiv: 2303.07245

Shevchenko, A., Kungurtsev, V., &; Mondelli, M. (2022). Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. Journal of Machine Learning Research.
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arXiv: 2111.02278

Zhang, Y., Jaggi, S., Langberg, M., &; Sarwate, A. D. (2022). The capacity of causal adversarial channels. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 2523–2528). Espoo, Finland: IEEE.https://doi.org/10.1109/ISIT50566.2022.9834709 
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arXiv: 2205.06708

Yadav, A. K., Alimohammadi, M., Zhang, Y., Budkuley, A. J., &; Jaggi, S. (2022). New results on AVCs with omniscient and myopic adversaries. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 2535–2540). Espoo, Finland: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/ISIT50566.2022.9834632 
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Joshi, P., Purkayastha, A., Zhang, Y., Budkuley, A. J., &; Jaggi, S. (2022). On the capacity of additive AVCs with feedback. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 504–509). Espoo, Finland: IEEE.https://doi.org/10.1109/ISIT50566.2022.9834850 
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Fathollahi, D., &; Mondelli, M. (2022). Polar coded computing: The role of the scaling exponent. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 2154–2159). Espoo, Finland: IEEE.https://doi.org/10.1109/ISIT50566.2022.9834712 
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arXiv: 2201.10082

Torkamani, S., Ebrahimi, J. B., Sadeghi, P., D’Oliveira, R. G. L., &; Médard, M. (2022). Heterogeneous differential privacy via graphs. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 1623–1628). Espoo, Finland: IEEE.https://doi.org/10.1109/ISIT50566.2022.9834711 
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arXiv: 2203.15429

Zhang, Y., &; Vatedka, S. (2022). Lower bounds on list decoding capacity using error exponents. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 1324–1329). Espoo, Finland: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/ISIT50566.2022.9834815 
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Zhang, Y., &; Vatedka, S. (2022). Lower bounds for multiple packing. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 3085–3090). Espoo, Finland: IEEE.https://doi.org/10.1109/ISIT50566.2022.9834443 
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Zhang, Y., &; Vatedka, S. (2022). List-decodability of Poisson Point Processes. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 2559–2564). Espoo, Finland: IEEE.https://doi.org/10.1109/ISIT50566.2022.9834512 
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Polyanskii, N., &; Zhang, Y. (2022). List-decodable zero-rate codes for the Z-channel. In 2022 IEEE International Symposium on Information Theory (Vol. 2022, pp. 2553–2558). Espoo, Finland: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/ISIT50566.2022.9834829 
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Venkataramanan, R., Kögler, K., &; Mondelli, M. (2022). Estimation in rotationally invariant generalized linear models via approximate message passing. In Proceedings of the 39th International Conference on Machine Learning (Vol. 162). Baltimore, MD, United States: ML Research Press.
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