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Marco Mondelli

Marek Jankola

Simone Bombari

Al Depope

Clementine Domine

Yijun Dong

Kevin Kögler

Filip Kovacevic

Cristina Lopez Amado

Pablo Pascual Cobo

Peter Sukenik

Diyuan Wu

Edwige Cyffers

Amedeo Esposito

Aleksandr Shevchenko

Yihan Zhang



85 Publications

2026 | Published | Journal Article | IST-REx-ID: 22228 | OA | PlanS
Zhang, Yihan, Marco Mondelli, and Ramji Venkataramanan. “Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models.” SIAM Journal on Mathematics of Data Science. Society for Industrial & Applied Mathematics, 2026. https://doi.org/10.1137/24m1702854.
[Published Version] View | Files available | DOI | arXiv
 
2026 | Published | Thesis | PhD | IST-REx-ID: 22258 | OA
Depope, Al. “From Sparse Selection to Risk Prediction : Approximate Message Passing for Proteomic Survival Models and Large-Scale Genomics.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22258.
[Published Version] View | Files available | DOI
 
2026 | Epub ahead of print | Journal Article | IST-REx-ID: 21488 | OA
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.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2025 | Published | Conference Paper | IST-REx-ID: 21324 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 21325 | OA
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.
[Published Version] View | Files available | PubMed | Europe PMC
 
2025 | Published | Conference Paper | IST-REx-ID: 21326 | OA
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] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 21328 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 18986 | OA
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.
[Published Version] View | Files available | DOI | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 19065 | OA | PlanS
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.
[Published Version] View | Files available | DOI | WoS
 
2025 | Published | Conference Paper | IST-REx-ID: 19281 | OA
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.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 19627 | OA
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.
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20033 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20035 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Epub ahead of print | Journal Article | IST-REx-ID: 20081 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20300 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2025 | Published | 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.
View | DOI
 
2025 | Published | Journal Article | IST-REx-ID: 20734 | OA | PlanS
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.
[Published Version] View | Files available | DOI
 
2024 | Published | Journal Article | IST-REx-ID: 14665 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2024 | Published | Journal Article | IST-REx-ID: 15172 | OA
Esposito, Amedeo Roberto, and Marco Mondelli. “Concentration without Independence via Information Measures.” IEEE Transactions on Information Theory. IEEE, 2024. https://doi.org/10.1109/TIT.2024.3367767.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
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.
View | DOI
 

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