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82 Publications


2025 | Published | Conference Paper | IST-REx-ID: 20033 | OA
Emrullah Ildiz, M., Gozeten, H. A., Taga, E. O., Mondelli, M., & Oymak, S. (2025). High-dimensional analysis of knowledge distillation: Weak-to-Strong generalization and scaling laws. In 13th International Conference on Learning Representations (pp. 2967–3006). Singapore, Singapore: ICLR.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20035 | OA
Jacot, A., Súkeník, P., Wang, Z., & Mondelli, M. (2025). Wide neural networks trained with weight decay provably exhibit neural collapse. In 13th International Conference on Learning Representations (pp. 1905–1931). Singapore, Singapore: ICLR.
[Published Version] View | Files available | arXiv
 

2025 | Epub ahead of print | Journal Article | IST-REx-ID: 20081 | OA
Esposito, A. R., Gastpar, M., & Issa, I. (2025). Sibson α-mutual information and its variational representations. IEEE Transactions on Information Theory. IEEE. https://doi.org/10.1109/TIT.2025.3587340
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20300 | OA
Wegel, T., Kovačević, F., Ţifrea, A., & Yang, F. (2025). Learning Pareto manifolds in high dimensions: How can regularization help? In The 28th International Conference on Artificial Intelligence and Statistics (Vol. 258, pp. 4591–4599). Mai Khao, Thailand: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20667
El Latif Kadry, A., Zhang, Y., & Weinberger, N. (2025). Mean estimation in high-dimensional binary timeinhomogeneous Markov Gaussian mixture models. In 2025 IEEE International Symposium on Information Theory Proceedings. Ann Arbor, MI, United States: IEEE. https://doi.org/10.1109/ISIT63088.2025.11195426
View | DOI
 

2025 | Published | Journal Article | IST-REx-ID: 20734 | OA | PlanS
Zhang, Y., Ji, H. C., Venkataramanan, R., & Mondelli, M. (2025). Spectral estimators for structured generalized linear models via approximate message passing. Mathematical Statistics and Learning. EMS Press. https://doi.org/10.4171/MSL/52
[Published Version] View | Files available | DOI
 

2025 | Published | Journal Article | IST-REx-ID: 18986 | OA
Barbier, J., Camilli, F., Xu, Y., & Mondelli, M. (2025). Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise. Physical Review Research. American Physical Society. https://doi.org/10.1103/PhysRevResearch.7.013081
[Published Version] View | Files available | DOI | arXiv
 

2025 | Published | Journal Article | IST-REx-ID: 19065 | OA | PlanS
Fornasier, M., Klock, T., Mondelli, M., & Rauchensteiner, M. (2025). Efficient identification of wide shallow neural networks with biases. Applied and Computational Harmonic Analysis. Elsevier. https://doi.org/10.1016/j.acha.2025.101749
[Published Version] View | Files available | DOI | WoS
 

2025 | Published | Conference Paper | IST-REx-ID: 19281 | OA
Resch, N., Yuan, C., & Zhang, Y. (2025). Tight bounds on list-decodable and list-recoverable zero-rate codes. In 16th Innovations in Theoretical Computer Science Conference (Vol. 325). New York, NY, United States: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ITCS.2025.82
[Published Version] View | Files available | DOI | WoS | arXiv
 

2025 | Published | Journal Article | IST-REx-ID: 19627 | OA
Bombari, S., & Mondelli, M. (2025). Privacy for free in the overparameterized regime. Proceedings of the National Academy of Sciences. National Academy of Sciences. https://doi.org/10.1073/pnas.2423072122
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21324 | OA
Bombari, S., & Mondelli, M. (2025). Spurious correlations in high dimensional regression: The roles of regularization, simplicity bias and over-parameterization. In Proceedings of the 42nd International Conference on Machine Learning (Vol. 267, pp. 4839–4873). Vancouver, Canada: ML Research Press.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21325 | OA
Gozeten, H. A., Ildiz, M. E., Zhang, X., Soltanolkotabi, M., Mondelli, M., & Oymak, S. (2025). Test-time training provably improves transformers as in-context learners. In Proceedings of the 42nd International Conference on Machine Learning (Vol. 267, pp. 20266–20295). Vancouver, Canada: ML Research Press.
[Published Version] View | Files available | PubMed | Europe PMC
 

2025 | Published | Conference Paper | IST-REx-ID: 21326 | OA
Wu, D., & Mondelli, M. (2025). Neural collapse beyond the unconstrained features model: Landscape, dynamics, and generalization in the mean-field regime. In Proceedings of the 42nd International Conference on Machine Learning (Vol. 267, pp. 67499–67536). Vancouver, Canada: ML Research Press.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21328 | OA
Kovačević, F., Yihan, Z., & Mondelli, M. (2025). Spectral estimators for multi-index models: Precise asymptotics and optimal weak recovery. In Proceedings of 38th Conference on Learning Theory (Vol. 291, pp. 3354–3404). Lyon, France: ML Research Press.
[Published Version] View | Files available | arXiv
 

2024 | Published | Journal Article | IST-REx-ID: 14665 | OA
Zhang, Y., & Vatedka, S. (2024). Multiple packing: Lower bounds via error exponents. IEEE Transactions on Information Theory. IEEE. https://doi.org/10.1109/TIT.2023.3334032
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 17893 | OA
Jin, L., Esposito, A. R., & Gastpar, M. (2024). Properties of the strong data processing constant for Rényi divergence. In Proceedings of the 2024 IEEE International Symposium on Information Theory (pp. 3178–3183). Athens, Greece: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISIT57864.2024.10619367
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 17894
Esposito, A. R., Gastpar, M., & Issa, I. (2024). Variational characterizations of Sibson’s α-mutual information. In Proceedings of the 2024 IEEE International Symposium on Information Theory (pp. 2110–2115). Athens, Greece: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISIT57864.2024.10619378
View | DOI | WoS
 

2024 | Published | Conference Paper | IST-REx-ID: 17895
Dey, B. K., Jaggi, S., Langberg, M., Sarwate, A. D., & Zhang, Y. (2024). Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs. In Proceedings of the 2024 IEEE International Symposium on Information Theory (pp. 1586–1591). Athens, Greece: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISIT57864.2024.10619362
View | DOI | WoS
 

2024 | Published | Journal Article | IST-REx-ID: 18652
Dey, B. K., Jaggi, S., Langberg, M., Sarwate, A. D., & Zhang, Y. (2024). Codes for adversaries: Between worst-case and average-case jamming. Foundations and Trends in Communications and Information Theory. Now Publishers. https://doi.org/10.1561/0100000112
View | DOI
 

2024 | Published | Conference Paper | IST-REx-ID: 18890 | OA
Beaglehole, D., Súkeník, P., Mondelli, M., & Belkin, M. (2024). Average gradient outer product as a mechanism for deep neural collapse. In 38th Annual Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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