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

Zhang Y, Vatedka S. Lower bounds on list decoding capacity using error exponents. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. Institute of Electrical and Electronics Engineers; 2022:1324-1329. doi:10.1109/ISIT50566.2022.9834815

Zhang Y, Vatedka S. Lower bounds for multiple packing. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE; 2022:3085-3090. doi:10.1109/ISIT50566.2022.9834443

Zhang Y, Vatedka S. List-decodability of Poisson Point Processes. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE; 2022:2559-2564. doi:10.1109/ISIT50566.2022.9834512

Polyanskii N, Zhang Y. List-decodable zero-rate codes for the Z-channel. In: 2022 IEEE International Symposium on Information Theory. Vol 2022. Institute of Electrical and Electronics Engineers; 2022:2553-2558. doi:10.1109/ISIT50566.2022.9834829

Venkataramanan R, Kögler K, Mondelli M. Estimation in rotationally invariant generalized linear models via approximate message passing. In: Proceedings of the 39th International Conference on Machine Learning. Vol 162. ML Research Press; 2022.

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

Bombari S, Achille A, Wang Z, et al. Towards differential relational privacy and its use in question answering. arXiv. doi:10.48550/arXiv.2203.16701

Zhang Y, Vatedka S. List decoding random Euclidean codes and Infinite constellations. IEEE Transactions on Information Theory. 2022;68(12):7753-7786. doi:10.1109/TIT.2022.3189542

Doan N, Hashemi SA, Mondelli M, Gross WJ. Decoding Reed-Muller codes with successive codeword permutations. IEEE Transactions on Communications. 2022;70(11):7134-7145. doi:10.1109/tcomm.2022.3211101

Zhang Y, Vatedka S, Jaggi S, Sarwate AD. Quadratically constrained myopic adversarial channels. IEEE Transactions on Information Theory. 2022;68(8):4901-4948. doi:10.1109/tit.2022.3167554

Hashemi SA, Mondelli M, Fazeli A, Vardy A, Cioffi J, Goldsmith A. Parallelism versus latency in simplified successive-cancellation decoding of polar codes. IEEE Transactions on Wireless Communications. 2022;21(6):3909-3920. doi:10.1109/TWC.2021.3125626

Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop. 2022:588-593. doi:10.1109/ITW54588.2022.9965870

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

Mondelli M, Venkataramanan R. Approximate message passing with spectral initialization for generalized linear models. Journal of Statistical Mechanics: Theory and Experiment. 2022;2022(11). doi:10.1088/1742-5468/ac9828

Nguyen Q, Mondelli M, Montufar GF. Tight bounds on the smallest eigenvalue of the neural tangent kernel for deep ReLU networks. In: Meila M, Zhang T, eds. Proceedings of the 38th International Conference on Machine Learning. Vol 139. ML Research Press; 2021:8119-8129.

Hashemi SA, Mondelli M, Cioffi J, Goldsmith A. Successive syndrome-check decoding of polar codes. In: Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers. Vol 2021-October. Institute of Electrical and Electronics Engineers; 2021:943-947. doi:10.1109/IEEECONF53345.2021.9723394

Nguyen Q, Mondelli M, Montufar G. 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. ML Research Press; 2021:8119-8129.

Mondelli M, Hashemi SA, Cioffi JM, Goldsmith A. Sublinear latency for simplified successive cancellation decoding of polar codes. IEEE Transactions on Wireless Communications. 2021;20(1):18-27. doi:10.1109/TWC.2020.3022922

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

Fathollahi D, Farsad N, Hashemi SA, Mondelli M. Sparse multi-decoder recursive projection aggregation for Reed-Muller codes. In: 2021 IEEE International Symposium on Information Theory. Institute of Electrical and Electronics Engineers; 2021:1082-1087. doi:10.1109/isit45174.2021.9517887

Mondelli M, Thrampoulidis C, Venkataramanan R. Optimal combination of linear and spectral estimators for generalized linear models. Foundations of Computational Mathematics. 2021. doi:10.1007/s10208-021-09531-x

Mondelli M, Venkataramanan R. PCA initialization for approximate message passing in rotationally invariant models. In: 35th Conference on Neural Information Processing Systems. Vol 35. Neural Information Processing Systems Foundation; 2021:29616-29629.

Nguyen Q, Bréchet P, Mondelli M. When are solutions connected in deep networks? In: 35th Conference on Neural Information Processing Systems. Vol 35. Neural Information Processing Systems Foundation; 2021.

Mondelli M, Venkataramanan R. Approximate message passing with spectral initialization for generalized linear models. In: Banerjee A, Fukumizu K, eds. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. Vol 130. ML Research Press; 2021:397-405.

Fazeli A, Hassani H, Mondelli M, Vardy A. Binary linear codes with optimal scaling: Polar codes with large kernels. IEEE Transactions on Information Theory. 2021;67(9):5693-5710. doi:10.1109/TIT.2020.3038806

Li S, Bitar R, Jaggi S, Zhang Y. Network coding with myopic adversaries. IEEE Journal on Selected Areas in Information Theory. 2021;2(4):1108-1119. doi:10.1109/JSAIT.2021.3126474

Nguyen Q, Mondelli M. Global convergence of deep networks with one wide layer followed by pyramidal topology. In: 34th Conference on Neural Information Processing Systems. Vol 33. Curran Associates; 2020:11961–11972.

Mondelli M, Hashemi SA, Cioffi J, Goldsmith A. Simplified successive cancellation decoding of polar codes has sublinear latency. In: IEEE International Symposium on Information Theory - Proceedings. Vol 2020-June. IEEE; 2020. doi:10.1109/ISIT44484.2020.9174141

Shevchenko A, Mondelli M. Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks. In: Proceedings of the 37th International Conference on Machine Learning. Vol 119. ML Research Press; 2020:8773-8784.

Javanmard A, Mondelli M, Montanari A. Analysis of a two-layer neural network via displacement convexity. Annals of Statistics. 2020;48(6):3619-3642. doi:10.1214/20-AOS1945

Hashemi SA, Condo C, Mondelli M, Gross WJ. Rate-flexible fast polar decoders. IEEE Transactions on Signal Processing. 2019;67(22). doi:10.1109/TSP.2019.2944738

Mondelli M, Hassani SH, Urbanke R. A new coding paradigm for the primitive relay channel. Algorithms. 2019;12(10). doi:10.3390/a12100218