Esposito, Amedeo Roberto, and Marco Mondelli. “Concentration without Independence via Information Measures.”https://doi.org/10.1109/TIT.2024.3367767__IEEE Transactions on Information Theory. IEEE, n.d.https://doi.org/10.1109/TIT.2024.3367767 .

Resch, Nicolas, Chen Yuan, and Yihan Zhang. “Zero-Rate Thresholds and New Capacity Bounds for List-Decoding and List-Recovery.”https://doi.org/10.4230/LIPIcs.ICALP.2023.99__In 50th International Colloquium on Automata, Languages, and Programming, Vol. 261. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023.https://doi.org/10.4230/LIPIcs.ICALP.2023.99 .

Barbier, Jean, Francesco Camilli, Marco Mondelli, and Manuel Sáenz. “Fundamental Limits in Structured Principal Component Analysis and How to Reach Them.”https://doi.org/10.1073/pnas.2302028120__Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences, 2023.https://doi.org/10.1073/pnas.2302028120 .

Shevchenko, Aleksandr, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.

Zhang, Yihan, and Shashank Vatedka. “Multiple Packing: Lower Bounds via Infinite Constellations.”https://doi.org/10.1109/TIT.2023.3260950__IEEE Transactions on Information Theory. IEEE, 2023.https://doi.org/10.1109/TIT.2023.3260950 .

Xu, Yizhou, Tian Qi Hou, Shan Suo Liang, and Marco Mondelli. “Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models.”https://doi.org/10.1109/ITW55543.2023.10160238__In 2023 IEEE Information Theory Workshop, 294–98. Institute of Electrical and Electronics Engineers, 2023.https://doi.org/10.1109/ITW55543.2023.10160238 .

Zhang, Yihan, and Shashank Vatedka. “Multiple Packing: Lower Bounds via Error Exponents.”https://doi.org/10.1109/TIT.2023.3334032__IEEE Transactions on Information Theory. IEEE, 2023.https://doi.org/10.1109/TIT.2023.3334032 .

Zhang, Yihan. “Zero-Error Communication over Adversarial MACs.”https://doi.org/10.1109/tit.2023.3257239__IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers, 2023.https://doi.org/10.1109/tit.2023.3257239 .

Polyanskii, Nikita, and Yihan Zhang. “Codes for the Z-Channel.”https://doi.org/10.1109/TIT.2023.3292219__IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers, 2023.https://doi.org/10.1109/TIT.2023.3292219 .

Bombari, Simone, Shayan Kiyani, and Marco Mondelli. “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, 202:2738–76. ML Research Press, 2023.

Súkeník, Peter, Marco Mondelli, and Christoph Lampert. “Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model.” In 37th Annual Conference on Neural Information Processing Systems, n.d.

Wu, Diyuan, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis for Heavy Ball Methods: Dropout-Stability, Connectivity, and Global Convergence.” In Transactions on Machine Learning Research. ML Research Press, 2023.

Fu, Teng, YuHao Liu, Jean Barbier, Marco Mondelli, ShanSuo Liang, and TianQi Hou. “Mismatched Estimation of Non-Symmetric Rank-One Matrices Corrupted by Structured Noise.”https://doi.org/10.1109/isit54713.2023.10206671__In Proceedings of 2023 IEEE International Symposium on Information Theory. IEEE, n.d.https://doi.org/10.1109/isit54713.2023.10206671 .

Esposito, Amedeo Roberto, and Marco Mondelli. “Concentration without Independence via Information Measures.”https://doi.org/10.1109/isit54713.2023.10206899__In Proceedings of 2023 IEEE International Symposium on Information Theory, 400–405. IEEE, 2023.https://doi.org/10.1109/isit54713.2023.10206899 .

Shevchenko, Aleksandr, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2022.

Zhang, Yihan, Sidharth Jaggi, Michael Langberg, and Anand D. Sarwate. “The Capacity of Causal Adversarial Channels.”https://doi.org/10.1109/ISIT50566.2022.9834709__In 2022 IEEE International Symposium on Information Theory, 2022:2523–28. IEEE, 2022.https://doi.org/10.1109/ISIT50566.2022.9834709 .

Yadav, Anuj Kumar, Mohammadreza Alimohammadi, Yihan Zhang, Amitalok J. Budkuley, and Sidharth Jaggi. “New Results on AVCs with Omniscient and Myopic Adversaries.”https://doi.org/10.1109/ISIT50566.2022.9834632__In 2022 IEEE International Symposium on Information Theory, 2022:2535–40. Institute of Electrical and Electronics Engineers, 2022.https://doi.org/10.1109/ISIT50566.2022.9834632 .

Joshi, Pranav, Amritakshya Purkayastha, Yihan Zhang, Amitalok J. Budkuley, and Sidharth Jaggi. “On the Capacity of Additive AVCs with Feedback.”https://doi.org/10.1109/ISIT50566.2022.9834850__In 2022 IEEE International Symposium on Information Theory, 2022:504–9. IEEE, 2022.https://doi.org/10.1109/ISIT50566.2022.9834850 .

Fathollahi, Dorsa, and Marco Mondelli. “Polar Coded Computing: The Role of the Scaling Exponent.”https://doi.org/10.1109/ISIT50566.2022.9834712__In 2022 IEEE International Symposium on Information Theory, 2022:2154–59. IEEE, 2022.https://doi.org/10.1109/ISIT50566.2022.9834712 .

Torkamani, Sahel, Javad B. Ebrahimi, Parastoo Sadeghi, Rafael G.L. D’Oliveira, and Muriel Médard. “Heterogeneous Differential Privacy via Graphs.”https://doi.org/10.1109/ISIT50566.2022.9834711__In 2022 IEEE International Symposium on Information Theory, 2022:1623–28. IEEE, 2022.https://doi.org/10.1109/ISIT50566.2022.9834711 .