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61 Publications
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 |Epub ahead of print| 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. IEEE, 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 |Submitted| 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: 17893 |
L. Jin, A. R. Esposito, and M. Gastpar, “Properties of the strong data processing constant for Rényi divergence,” in Proceedings of the 2024 IEEE International Symposium on Information Theory, Athens, Greece, 2024, pp. 3178–3183.
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| arXiv
2024 |Published| Conference Paper | IST-REx-ID: 17895
B. K. Dey, S. Jaggi, M. Langberg, A. D. Sarwate, and Y. Zhang, “Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs,” in Proceedings of the 2024 IEEE International Symposium on Information Theory , Athens, Greece, 2024, pp. 1586–1591.
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2024 |Published| Conference Paper | IST-REx-ID: 17469 |
K. Kögler, A. Shevchenko, H. Hassani, and M. Mondelli, “Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 24964–25015.
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| arXiv
2024 |Published| Thesis | IST-REx-ID: 17465
A. Shevchenko, “High-dimensional limits in artificial neural networks,” Institute of Science and Technology Austria, 2024.
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2023 |Published| Journal Article | IST-REx-ID: 13315 |
J. Barbier, F. Camilli, M. Mondelli, and M. Sáenz, “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, vol. 120, no. 30. National Academy of Sciences, 2023.
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| PubMed | Europe PMC
2023 |Published| Journal Article | IST-REx-ID: 12838 |
Y. Zhang and S. Vatedka, “Multiple packing: Lower bounds via infinite constellations,” IEEE Transactions on Information Theory, vol. 69, no. 7. IEEE, pp. 4513–4527, 2023.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 13321 |
Y. Xu, T. Q. Hou, S. S. Liang, and M. Mondelli, “Approximate message passing for multi-layer estimation in rotationally invariant models,” in 2023 IEEE Information Theory Workshop, Saint-Malo, France, 2023, pp. 294–298.
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| arXiv
2023 |Published| Journal Article | IST-REx-ID: 14751 |
Y. Zhang, “Zero-error communication over adversarial MACs,” IEEE Transactions on Information Theory, vol. 69, no. 7. Institute of Electrical and Electronics Engineers, pp. 4093–4127, 2023.
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| arXiv
2023 |Published| Journal Article | IST-REx-ID: 13269 |
N. Polyanskii and Y. Zhang, “Codes for the Z-channel,” IEEE Transactions on Information Theory, vol. 69, no. 10. Institute of Electrical and Electronics Engineers, pp. 6340–6357, 2023.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 12859 |
S. Bombari, S. Kiyani, and M. Mondelli, “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, Honolulu, HI, United States, 2023, vol. 202, pp. 2738–2776.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 14924 |
D. Wu, V. Kungurtsev, and M. Mondelli, “Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence,” in Transactions on Machine Learning Research, 2023.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 14921 |
P. Súkeník, M. Mondelli, and C. Lampert, “Deep neural collapse is provably optimal for the deep unconstrained features model,” in 37th Annual Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2023.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 14923 |
T. Fu, Y. Liu, J. Barbier, M. Mondelli, S. Liang, and T. Hou, “Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise,” in Proceedings of 2023 IEEE International Symposium on Information Theory, Taipei, Taiwan, 2023, pp. 1178–1183.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 14083 |
N. Resch, C. Yuan, and Y. Zhang, “Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery,” in 50th International Colloquium on Automata, Languages, and Programming, Paderborn, Germany, 2023, vol. 261.
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