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77 Publications
2025 | Published | Journal Article | IST-REx-ID: 18986 | 
J. Barbier, F. Camilli, Y. Xu, and M. Mondelli, “Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise,” Physical Review Research, vol. 7. American Physical Society, 2025.
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| arXiv
2025 | Epub ahead of print | Journal Article | IST-REx-ID: 20081 |
A. R. Esposito, M. Gastpar, and I. Issa, “Sibson α-mutual information and its variational representations,” IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers, 2025.
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| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20033 |
M. Emrullah Ildiz, H. A. Gozeten, E. O. Taga, M. Mondelli, and S. Oymak, “High-dimensional analysis of knowledge distillation: Weak-to-Strong generalization and scaling laws,” in 13th International Conference on Learning Representations, Singapore, Singapore, 2025, pp. 2967–3006.
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| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20035 |
A. Jacot, P. Súkeník, Z. Wang, and M. Mondelli, “Wide neural networks trained with weight decay provably exhibit neural collapse,” in 13th International Conference on Learning Representations, Singapore, Singapore, 2025, pp. 1905–1931.
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| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20300 |
T. Wegel, F. Kovačević, A. Ţifrea, and F. Yang, “Learning Pareto manifolds in high dimensions: How can regularization help?,” in The 28th International Conference on Artificial Intelligence and Statistics, Mai Khao, Thailand, 2025, vol. 258, pp. 4591–4599.
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| arXiv
2025 | Published | Journal Article | IST-REx-ID: 19065 |
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M. Fornasier, T. Klock, M. Mondelli, and M. Rauchensteiner, “Efficient identification of wide shallow neural networks with biases,” Applied and Computational Harmonic Analysis, vol. 77. Elsevier, 2025.
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| WoS
2025 | Published | Conference Paper | IST-REx-ID: 19281 |
N. Resch, C. Yuan, and Y. Zhang, “Tight bounds on list-decodable and list-recoverable zero-rate codes,” in 16th Innovations in Theoretical Computer Science Conference, New York, NY, United States, 2025, vol. 325.
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| arXiv
2025 | Published | Journal Article | IST-REx-ID: 19627 |
S. Bombari and M. Mondelli, “Privacy for free in the overparameterized regime,” Proceedings of the National Academy of Sciences, vol. 122, no. 15. National Academy of Sciences, 2025.
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| PubMed | Europe PMC
| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20667
A. El Latif Kadry, Y. Zhang, and N. Weinberger, “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, 2025.
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2024 | Published | Journal Article | IST-REx-ID: 18652
B. K. Dey, S. Jaggi, M. Langberg, A. D. Sarwate, and Y. Zhang, “Codes for adversaries: Between worst-case and average-case jamming,” Foundations and Trends in Communications and Information Theory, vol. 21, no. 3–4. Now Publishers, pp. 300–588, 2024.
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2024 | Published | Conference Paper | IST-REx-ID: 18973 |
S. Bombari and M. Mondelli, “Towards understanding the word sensitivity of attention layers: A study via random features,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 4300–4328.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18972 |
S. Bombari and M. Mondelli, “How spurious features are memorized: Precise analysis for random and NTK features,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 4267–4299.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18897 |
F. Pedrotti, J. Maas, and M. Mondelli, “Improved convergence of score-based diffusion models via prediction-correction,” in Transactions on Machine Learning Research, 2024.
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| arXiv
2024 | Draft | Preprint | IST-REx-ID: 17350 |
F. Pedrotti, J. Maas, and M. Mondelli, “Improved convergence of score-based diffusion models via prediction-correction,” arXiv. .
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18890 |
D. Beaglehole, P. Súkeník, M. Mondelli, and M. Belkin, “Average gradient outer product as a mechanism for deep neural collapse,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19518 |
D. Wu, I.-V. Modoranu, M. Safaryan, D. Kuznedelev, and D.-A. Alistarh, “The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18891 |
P. Súkeník, C. Lampert, and M. Mondelli, “Neural collapse versus low-rank bias: Is deep neural collapse really optimal?,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
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| arXiv
2024 | Published | Journal Article | IST-REx-ID: 14665 |
Y. Zhang and S. Vatedka, “Multiple packing: Lower bounds via error exponents,” IEEE Transactions on Information Theory, vol. 70, no. 2. IEEE, pp. 1008–1039, 2024.
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| arXiv
2024 | Published | Journal Article | IST-REx-ID: 15172 |
A. R. Esposito and M. Mondelli, “Concentration without independence via information measures,” IEEE Transactions on Information Theory, vol. 70, no. 6. IEEE, pp. 3823–3839, 2024.
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| arXiv
2024 | Published | Journal Article | IST-REx-ID: 17330 |
N. Resch, C. Yuan, and Y. Zhang, “Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery,” IEEE Transactions on Information Theory, vol. 70, no. 9. IEEE, pp. 6211–6238, 2024.
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| arXiv