Esposito, A. R., &; Mondelli, M. (n.d.). Concentration without independence via information measures. IEEE Transactions on Information Theory. IEEE.https://doi.org/10.1109/TIT.2024.3367767 
LibreCat: https://research-explorer.ista.ac.at/record/15172
DOI: 10.1109/TIT.2024.3367767
arXiv: 2303.07245

Resch, N., Yuan, C., &; Zhang, Y. (2023). Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.ICALP.2023.99 
LibreCat: https://research-explorer.ista.ac.at/record/14083
DOI: 10.4230/LIPIcs.ICALP.2023.99
arXiv: 2210.07754

Barbier, J., Camilli, F., Mondelli, M., &; Sáenz, M. (2023). 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. National Academy of Sciences.https://doi.org/10.1073/pnas.2302028120 
LibreCat: https://research-explorer.ista.ac.at/record/13315
DOI: 10.1073/pnas.2302028120
PMID: 37463204

Shevchenko, A., Kögler, K., Hassani, H., &; Mondelli, M. (2023). Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 31151–31209). Honolulu, Hawaii, HI, United States: ML Research Press.
LibreCat: https://research-explorer.ista.ac.at/record/14459
arXiv: 2212.13468

Zhang, Y., &; Vatedka, S. (2023). Multiple packing: Lower bounds via infinite constellations. IEEE Transactions on Information Theory. IEEE.https://doi.org/10.1109/TIT.2023.3260950 
LibreCat: https://research-explorer.ista.ac.at/record/12838
DOI: 10.1109/TIT.2023.3260950
WoS: 001017307000023
arXiv: 2211.04407

Xu, Y., Hou, T. Q., Liang, S. S., &; Mondelli, M. (2023). Approximate message passing for multi-layer estimation in rotationally invariant models. In 2023 IEEE Information Theory Workshop (pp. 294–298). Saint-Malo, France: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/ITW55543.2023.10160238 
LibreCat: https://research-explorer.ista.ac.at/record/13321
DOI: 10.1109/ITW55543.2023.10160238
WoS: 001031733100053
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 
LibreCat: https://research-explorer.ista.ac.at/record/14665
DOI: 10.1109/TIT.2023.3334032
arXiv: 2211.04408

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 
LibreCat: https://research-explorer.ista.ac.at/record/14751
DOI: 10.1109/tit.2023.3257239
arXiv: 2101.12426

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 
LibreCat: https://research-explorer.ista.ac.at/record/13269
DOI: 10.1109/TIT.2023.3292219
WoS: 001069680100011
arXiv: 2105.01427

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.
LibreCat: https://research-explorer.ista.ac.at/record/12859
arXiv: 2302.01629

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.
LibreCat: https://research-explorer.ista.ac.at/record/14921
arXiv: 2305.13165

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.
LibreCat: https://research-explorer.ista.ac.at/record/14924
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 
LibreCat: https://research-explorer.ista.ac.at/record/14923
DOI: 10.1109/isit54713.2023.10206671
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 
LibreCat: https://research-explorer.ista.ac.at/record/14922
DOI: 10.1109/isit54713.2023.10206899
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.
LibreCat: https://research-explorer.ista.ac.at/record/11420
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 
LibreCat: https://research-explorer.ista.ac.at/record/12011
DOI: 10.1109/ISIT50566.2022.9834709
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 
LibreCat: https://research-explorer.ista.ac.at/record/12017
DOI: 10.1109/ISIT50566.2022.9834632

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 
LibreCat: https://research-explorer.ista.ac.at/record/12013
DOI: 10.1109/ISIT50566.2022.9834850

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 
LibreCat: https://research-explorer.ista.ac.at/record/12016
DOI: 10.1109/ISIT50566.2022.9834712
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 
LibreCat: https://research-explorer.ista.ac.at/record/12012
DOI: 10.1109/ISIT50566.2022.9834711
arXiv: 2203.15429