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71 Publications

2025 | Epub ahead of print | Journal Article | IST-REx-ID: 19065 | OA
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
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2025 | Published | Conference Paper | IST-REx-ID: 19281 | OA
Resch, Nicolas, Tight bounds on list-decodable and list-recoverable zero-rate codes. 16th Innovations in Theoretical Computer Science Conference 325. 2025
[Published Version] View | Files available | DOI | arXiv
 
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
 
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.) | 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
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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
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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
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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
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2024 | Published | Journal Article | IST-REx-ID: 17330 | OA
Resch, N., Yuan, C., & Zhang, Y. (2024). Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery. IEEE Transactions on Information Theory. IEEE. https://doi.org/10.1109/TIT.2024.3430842
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 19518 | OA
Wu, Diyuan, The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. 38th Conference on Neural Information Processing Systems 37. 2024
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18891 | OA
Súkeník, Peter, Neural collapse versus low-rank bias: Is deep neural collapse really optimal?. 38th Annual Conference on Neural Information Processing Systems 37. 2024
[Published Version] View | Files available
 
2024 | Published | Conference Paper | IST-REx-ID: 18890 | OA
Beaglehole, Daniel, Average gradient outer product as a mechanism for deep neural collapse. 38th Annual Conference on Neural Information Processing Systems 37. 2024
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18973 | OA
Bombari, S., & Mondelli, M. (2024). Towards understanding the word sensitivity of attention layers: A study via random features. In 41st International Conference on Machine Learning (Vol. 235, pp. 4300–4328). Vienna, Austria: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18972 | OA
Bombari, S., & Mondelli, M. (2024). How spurious features are memorized: Precise analysis for random and NTK features. In 41st International Conference on Machine Learning (Vol. 235, pp. 4267–4299). Vienna, Austria: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Journal Article | IST-REx-ID: 15172 | OA
Esposito, A. R., & Mondelli, M. (2024). Concentration without independence via information measures. IEEE Transactions on Information Theory. IEEE. https://doi.org/10.1109/TIT.2024.3367767
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17147
Depope, A., Mondelli, M., & Robinson, M. R. (2024). Inference of genetic effects via approximate message passing. In 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (pp. 13151–13155). Seoul, Korea: IEEE. https://doi.org/10.1109/ICASSP48485.2024.10447198
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2024 | Published | Conference Paper | IST-REx-ID: 18897 | OA
Pedrotti, F., Maas, J., & Mondelli, M. (2024). Improved convergence of score-based diffusion models via prediction-correction. In Transactions on Machine Learning Research.
[Published Version] View | Files available | arXiv
 
2024 | Draft | Preprint | IST-REx-ID: 17350 | OA
Pedrotti, F., Maas, J., & Mondelli, M. (n.d.). Improved convergence of score-based diffusion models via prediction-correction. arXiv. https://doi.org/10.48550/arXiv.2305.14164
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Thesis | IST-REx-ID: 17465 | OA
Shevchenko, A. (2024). High-dimensional limits in artificial neural networks. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:17465
[Published Version] View | Files available | DOI
 
2024 | Published | Conference Paper | IST-REx-ID: 17469 | OA
Kögler, K., Shevchenko, A., Hassani, H., & Mondelli, M. (2024). Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 24964–25015). Vienna, Austria: ML Research Press.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

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