Esposito AR, Mondelli M. Concentration without independence via information measures. IEEE Transactions on Information Theory. doi:10.1109/TIT.2024.3367767

Resch N, Yuan C, Zhang Y. Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery. In: 50th International Colloquium on Automata, Languages, and Programming. Vol 261. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023. doi:10.4230/LIPIcs.ICALP.2023.99

Barbier J, Camilli F, Mondelli M, Sáenz M. Fundamental limits in structured principal component analysis and how to reach them. Proceedings of the National Academy of Sciences of the United States of America. 2023;120(30). doi:10.1073/pnas.2302028120

Shevchenko A, Kögler K, Hassani H, Mondelli M. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:31151-31209.

Zhang Y, Vatedka S. Multiple packing: Lower bounds via infinite constellations. IEEE Transactions on Information Theory. 2023;69(7):4513-4527. doi:10.1109/TIT.2023.3260950

Xu Y, Hou TQ, Liang SS, Mondelli M. Approximate message passing for multi-layer estimation in rotationally invariant models. In: 2023 IEEE Information Theory Workshop. Institute of Electrical and Electronics Engineers; 2023:294-298. doi:10.1109/ITW55543.2023.10160238

Zhang Y, Vatedka S. Multiple packing: Lower bounds via error exponents. IEEE Transactions on Information Theory. 2023. doi:10.1109/TIT.2023.3334032

Zhang Y. Zero-error communication over adversarial MACs. IEEE Transactions on Information Theory. 2023;69(7):4093-4127. doi:10.1109/tit.2023.3257239

Polyanskii N, Zhang Y. Codes for the Z-channel. IEEE Transactions on Information Theory. 2023;69(10):6340-6357. doi:10.1109/TIT.2023.3292219

Bombari S, Kiyani S, Mondelli M. 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. ML Research Press; 2023:2738-2776.

Súkeník P, Mondelli M, Lampert C. Deep neural collapse is provably optimal for the deep unconstrained features model. In: 37th Annual Conference on Neural Information Processing Systems.

Wu D, Kungurtsev V, Mondelli M. Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. In: Transactions on Machine Learning Research. ML Research Press; 2023.

Fu T, Liu Y, Barbier J, Mondelli M, Liang S, Hou T. Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. In: Proceedings of 2023 IEEE International Symposium on Information Theory. IEEE. doi:10.1109/isit54713.2023.10206671

Esposito AR, Mondelli M. Concentration without independence via information measures. In: Proceedings of 2023 IEEE International Symposium on Information Theory. IEEE; 2023:400-405. doi:10.1109/isit54713.2023.10206899

Shevchenko A, Kungurtsev V, Mondelli M. Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. 2022;23(130):1-55.

Zhang Y, Jaggi S, Langberg M, Sarwate AD. The capacity of causal adversarial channels. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE; 2022:2523-2528. doi:10.1109/ISIT50566.2022.9834709

Yadav AK, Alimohammadi M, Zhang Y, Budkuley AJ, Jaggi S. New results on AVCs with omniscient and myopic adversaries. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. Institute of Electrical and Electronics Engineers; 2022:2535-2540. doi:10.1109/ISIT50566.2022.9834632

Joshi P, Purkayastha A, Zhang Y, Budkuley AJ, Jaggi S. On the capacity of additive AVCs with feedback. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE; 2022:504-509. doi:10.1109/ISIT50566.2022.9834850

Fathollahi D, Mondelli M. Polar coded computing: The role of the scaling exponent. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE; 2022:2154-2159. doi:10.1109/ISIT50566.2022.9834712

Torkamani S, Ebrahimi JB, Sadeghi P, D’Oliveira RGL, Médard M. Heterogeneous differential privacy via graphs. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE; 2022:1623-1628. doi:10.1109/ISIT50566.2022.9834711