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 

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 

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 

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 

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.

Barbier, J., Hou, T., Mondelli, M., &; Saenz, M. (n.d.). The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation? arXiv.https://doi.org/10.48550/arXiv.2205.10009 

Bombari, S., Achille, A., Wang, Z., Wang, Y.-X., Xie, Y., Singh, K. Y.,https://doi.org/10.48550/arXiv.2203.16701__Soatto, S. (n.d.). Towards differential relational privacy and its use in question answering. arXiv.https://doi.org/10.48550/arXiv.2203.16701 

Zhang, Y., &; Vatedka, S. (2022). List decoding random Euclidean codes and Infinite constellations. IEEE Transactions on Information Theory. IEEE.https://doi.org/10.1109/TIT.2022.3189542 

Doan, N., Hashemi, S. A., Mondelli, M., &; Gross, W. J. (2022). Decoding Reed-Muller codes with successive codeword permutations. IEEE Transactions on Communications. Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/tcomm.2022.3211101 

Zhang, Y., Vatedka, S., Jaggi, S., &; Sarwate, A. D. (2022). Quadratically constrained myopic adversarial channels. IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/tit.2022.3167554 

Hashemi, S. A., Mondelli, M., Fazeli, A., Vardy, A., Cioffi, J., &; Goldsmith, A. (2022). Parallelism versus latency in simplified successive-cancellation decoding of polar codes. IEEE Transactions on Wireless Communications. Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/TWC.2021.3125626 

Amani, M. H., Bombari, S., Mondelli, M., Pukdee, R., &; Rini, S. (2022). Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop. Mumbai, India: IEEE.https://doi.org/10.1109/ITW54588.2022.9965870 

Bombari, S., Amani, M. H., &; Mondelli, M. (2022). Memorization and optimization in deep neural networks with minimum over-parameterization. In 36th Conference on Neural Information Processing Systems (Vol. 35, pp. 7628–7640). Curran Associates.

Mondelli, M., &; Venkataramanan, R. (2022). Approximate message passing with spectral initialization for generalized linear models. Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing.https://doi.org/10.1088/1742-5468/ac9828 

Mondelli, M., Thrampoulidis, C., &; Venkataramanan, R. (2022). Optimal combination of linear and spectral estimators for generalized linear models. Foundations of Computational Mathematics. Springer.https://doi.org/10.1007/s10208-021-09531-x 

Nguyen, Q., Mondelli, M., &; Montufar, G. F. (2021). Tight bounds on the smallest eigenvalue of the neural tangent kernel for deep ReLU networks. In M. Meila &; T. Zhang (Eds.), Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 8119–8129). Virtual: ML Research Press.

Hashemi, S. A., Mondelli, M., Cioffi, J., &; Goldsmith, A. (2021). Successive syndrome-check decoding of polar codes. In Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers (Vol. 2021–October, pp. 943–947). Virtual, Pacific Grove, CA, United States: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/IEEECONF53345.2021.9723394 

Nguyen, Q., Mondelli, M., &; Montufar, G. (2021). Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks. In Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 8119–8129). Virtual: ML Research Press.

Mondelli, M., Hashemi, S. A., Cioffi, J. M., &; Goldsmith, A. (2021). Sublinear latency for simplified successive cancellation decoding of polar codes. IEEE Transactions on Wireless Communications. IEEE.https://doi.org/10.1109/TWC.2020.3022922 

Hashemi, S. A., Mondelli, M., Fazeli, A., Vardy, A., Cioffi, J., &; Goldsmith, A. (2021). Parallelism versus latency in simplified successive-cancellation decoding of polar codes. In 2021 IEEE International Symposium on Information Theory (pp. 2369–2374). Melbourne, Australia: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/ISIT45174.2021.9518153