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72 Publications

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
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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
 
2023 | Published | Journal Article | IST-REx-ID: 13269 | OA
Polyanskii, N., & Zhang, Y. (2023). Codes for the Z-channel. IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/TIT.2023.3292219
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Published | Journal Article | IST-REx-ID: 12838 | OA
Zhang, Y., & Vatedka, S. (2023). Multiple packing: Lower bounds via infinite constellations. IEEE Transactions on Information Theory. IEEE. https://doi.org/10.1109/TIT.2023.3260950
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Published | Journal Article | IST-REx-ID: 14751 | OA
Zhang, Y. (2023). Zero-error communication over adversarial MACs. IEEE Transactions on Information Theory. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/tit.2023.3257239
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 14083 | OA
Resch, Nicolas, Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery. 50th International Colloquium on Automata, Languages, and Programming 261. 2023
[Published Version] View | Files available | DOI | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 14923 | OA
Fu, Teng, Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. Proceedings of 2023 IEEE International Symposium on Information Theory. 2023
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 14922 | OA
Esposito, Amedeo Roberto, Concentration without independence via information measures. Proceedings of 2023 IEEE International Symposium on Information Theory. 2023
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2023 | Published | Journal Article | IST-REx-ID: 13315 | OA
Barbier, J., Camilli, F., Mondelli, M., & Sáenz, M. (2023). Fundamental limits in structured principal component analysis and how to reach them. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.2302028120
[Published Version] View | Files available | DOI | PubMed | Europe PMC
 
2023 | Published | Conference Paper | IST-REx-ID: 13321 | OA
Xu, Y., Hou, T. Q., Liang, S. S., & Mondelli, M. (2023). Approximate message passing for multi-layer estimation in rotationally invariant models. In 2023 IEEE Information Theory Workshop (pp. 294–298). Saint-Malo, France: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ITW55543.2023.10160238
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 12859 | OA
Bombari, S., Kiyani, S., & Mondelli, M. (2023). Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 2738–2776). Honolulu, HI, United States: ML Research Press.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

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