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83 Publications
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2026 |
Epub ahead of print |
Journal Article |
IST-REx-ID: 21488 |
Depope, Al, Jakub Bajzik, Marco Mondelli, and Matthew Richard Robinson. “Joint Modeling of Whole-Genome Sequencing Data for Human Height via Approximate Message Passing.” Cell Genomics. Elsevier, 2026. https://doi.org/10.1016/j.xgen.2026.101162.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 20033 |
Emrullah Ildiz, M., Halil Alperen Gozeten, Ege Onur Taga, Marco Mondelli, and Samet Oymak. “High-Dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws.” In 13th International Conference on Learning Representations, 2967–3006. ICLR, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20035 |
Jacot, Arthur, Peter Súkeník, Zihan Wang, and Marco Mondelli. “Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse.” In 13th International Conference on Learning Representations, 1905–31. ICLR, 2025.
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| arXiv
2025 |
Epub ahead of print |
Journal Article |
IST-REx-ID: 20081 |
Esposito, Amedeo Roberto, Michael Gastpar, and Ibrahim Issa. “Sibson α-Mutual Information and Its Variational Representations.” IEEE Transactions on Information Theory. IEEE, 2025. https://doi.org/10.1109/TIT.2025.3587340.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20300 |
Wegel, Tobias, Filip Kovačević, Alexandru Ţifrea, and Fanny Yang. “Learning Pareto Manifolds in High Dimensions: How Can Regularization Help?” In The 28th International Conference on Artificial Intelligence and Statistics, 258:4591–99. ML Research Press, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20667
El Latif Kadry, Abd, Yihan Zhang, and Nir Weinberger. “Mean Estimation in High-Dimensional Binary Timeinhomogeneous Markov Gaussian Mixture Models.” In 2025 IEEE International Symposium on Information Theory Proceedings. IEEE, 2025. https://doi.org/10.1109/ISIT63088.2025.11195426.
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2025 |
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Journal Article |
IST-REx-ID: 20734 |
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Zhang, Yihan, Hong Chang Ji, Ramji Venkataramanan, and Marco Mondelli. “Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing.” Mathematical Statistics and Learning. EMS Press, 2025. https://doi.org/10.4171/MSL/52.
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2025 |
Published |
Journal Article |
IST-REx-ID: 18986 |
Barbier, Jean, Francesco Camilli, Yizhou Xu, and Marco Mondelli. “Information Limits and Thouless-Anderson-Palmer Equations for Spiked Matrix Models with Structured Noise.” Physical Review Research. American Physical Society, 2025. https://doi.org/10.1103/PhysRevResearch.7.013081.
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| arXiv
2025 |
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Journal Article |
IST-REx-ID: 19065 |
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Fornasier, Massimo, Timo Klock, Marco Mondelli, and Michael Rauchensteiner. “Efficient Identification of Wide Shallow Neural Networks with Biases.” Applied and Computational Harmonic Analysis. Elsevier, 2025. https://doi.org/10.1016/j.acha.2025.101749.
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2025 |
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Conference Paper |
IST-REx-ID: 19281 |
Resch, Nicolas, Chen Yuan, and Yihan Zhang. “Tight Bounds on List-Decodable and List-Recoverable Zero-Rate Codes.” In 16th Innovations in Theoretical Computer Science Conference, Vol. 325. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025. https://doi.org/10.4230/LIPIcs.ITCS.2025.82.
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| arXiv
2025 |
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Journal Article |
IST-REx-ID: 19627 |
Bombari, Simone, and Marco Mondelli. “Privacy for Free in the Overparameterized Regime.” Proceedings of the National Academy of Sciences. National Academy of Sciences, 2025. https://doi.org/10.1073/pnas.2423072122.
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| PubMed | Europe PMC
| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 21324 |
Bombari, Simone, and Marco Mondelli. “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, 267:4839–73. ML Research Press, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 21325 |
Gozeten, Halil Alperen, Muhammed Emrullah Ildiz, Xuechen Zhang, Mahdi Soltanolkotabi, Marco Mondelli, and Samet Oymak. “Test-Time Training Provably Improves Transformers as in-Context Learners.” In Proceedings of the 42nd International Conference on Machine Learning, 267:20266–95. ML Research Press, 2025.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 21326 |
Wu, Diyuan, and Marco Mondelli. “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, 267:67499–536. ML Research Press, 2025.
[Published Version]
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 21328 |
Kovačević, Filip, Zhang Yihan, and Marco Mondelli. “Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery.” In Proceedings of 38th Conference on Learning Theory, 291:3354–3404. ML Research Press, 2025.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 14665 |
Zhang, Yihan, and Shashank Vatedka. “Multiple Packing: Lower Bounds via Error Exponents.” IEEE Transactions on Information Theory. IEEE, 2024. https://doi.org/10.1109/TIT.2023.3334032.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17893 |
Jin, Lifu, Amedeo Roberto Esposito, and Michael Gastpar. “Properties of the Strong Data Processing Constant for Rényi Divergence.” In Proceedings of the 2024 IEEE International Symposium on Information Theory, 3178–83. Institute of Electrical and Electronics Engineers, 2024. https://doi.org/10.1109/ISIT57864.2024.10619367.
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2024 |
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Conference Paper |
IST-REx-ID: 17894
Esposito, Amedeo Roberto, Michael Gastpar, and Ibrahim Issa. “Variational Characterizations of Sibson’s α-Mutual Information.” In Proceedings of the 2024 IEEE International Symposium on Information Theory , 2110–15. Institute of Electrical and Electronics Engineers, 2024. https://doi.org/10.1109/ISIT57864.2024.10619378.
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2024 |
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Conference Paper |
IST-REx-ID: 17895
Dey, B. K., S. Jaggi, M. Langberg, A. D. Sarwate, and Yihan Zhang. “Computationally Efficient Codes for Strongly Dobrushin-Stambler Nonsymmetrizable Oblivious AVCs.” In Proceedings of the 2024 IEEE International Symposium on Information Theory , 1586–91. Institute of Electrical and Electronics Engineers, 2024. https://doi.org/10.1109/ISIT57864.2024.10619362.
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2024 |
Published |
Journal Article |
IST-REx-ID: 18652
Dey, Bikash Kumar, Sidharth Jaggi, Michael Langberg, Anand D. Sarwate, and Yihan Zhang. “Codes for Adversaries: Between Worst-Case and Average-Case Jamming.” Foundations and Trends in Communications and Information Theory. Now Publishers, 2024. https://doi.org/10.1561/0100000112.
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