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Clementine Domine

Kevin Kögler

Simone Bombari

Diyuan Wu

Marco Mondelli

Peter Sukenik

Al Depope

Aleksandr Shevchenko

Yihan Zhang

Amedeo Esposito



72 Publications

2025 | Epub ahead of print | Journal Article | IST-REx-ID: 19065 | OA
Efficient identification of wide shallow neural networks with biases
M. Fornasier, T. Klock, M. Mondelli, M. Rauchensteiner, Applied and Computational Harmonic Analysis 77 (2025).
[Published Version] View | DOI | Download Published Version (ext.)
 
2025 | Published | Conference Paper | IST-REx-ID: 19281 | OA
Tight bounds on list-decodable and list-recoverable zero-rate codes
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
Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise
J. Barbier, F. Camilli, Y. Xu, M. Mondelli, Physical Review Research 7 (2025).
[Published Version] View | Files available | DOI | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 19627 | OA
Privacy for free in the overparameterized regime
S. Bombari, M. Mondelli, Proceedings of the National Academy of Sciences 122 (2025).
[Published Version] View | Files available | DOI | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17893 | OA
Properties of the strong data processing constant for Rényi divergence
L. Jin, A.R. Esposito, M. Gastpar, in:, Proceedings of the 2024 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2024, pp. 3178–3183.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17894
Variational characterizations of Sibson's α-mutual information
A.R. Esposito, M. Gastpar, I. Issa, in:, Proceedings of the 2024 IEEE International Symposium on Information Theory , Institute of Electrical and Electronics Engineers, 2024, pp. 2110–2115.
View | DOI
 
2024 | Published | Conference Paper | IST-REx-ID: 17895
Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs
B.K. Dey, S. Jaggi, M. Langberg, A.D. Sarwate, Y. Zhang, in:, Proceedings of the 2024 IEEE International Symposium on Information Theory , Institute of Electrical and Electronics Engineers, 2024, pp. 1586–1591.
View | DOI
 
2024 | Published | Journal Article | IST-REx-ID: 14665 | OA
Multiple packing: Lower bounds via error exponents
Y. Zhang, S. Vatedka, IEEE Transactions on Information Theory 70 (2024) 1008–1039.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Journal Article | IST-REx-ID: 18652
Codes for adversaries: Between worst-case and average-case jamming
B.K. Dey, S. Jaggi, M. Langberg, A.D. Sarwate, Y. Zhang, Foundations and Trends in Communications and Information Theory 21 (2024) 300–588.
View | DOI
 
2024 | Published | Journal Article | IST-REx-ID: 17330 | OA
Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery
N. Resch, C. Yuan, Y. Zhang, IEEE Transactions on Information Theory 70 (2024) 6211–6238.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 19518 | OA
The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information
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
Neural collapse versus low-rank bias: Is deep neural collapse really optimal?
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
Average gradient outer product as a mechanism for deep neural collapse
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
Towards understanding the word sensitivity of attention layers: A study via random features
S. Bombari, M. Mondelli, in:, 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 4300–4328.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18972 | OA
How spurious features are memorized: Precise analysis for random and NTK features
S. Bombari, M. Mondelli, in:, 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 4267–4299.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Journal Article | IST-REx-ID: 15172 | OA
Concentration without independence via information measures
A.R. Esposito, M. Mondelli, IEEE Transactions on Information Theory 70 (2024) 3823–3839.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17147
Inference of genetic effects via approximate message passing
A. Depope, M. Mondelli, M.R. Robinson, in:, 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, 2024, pp. 13151–13155.
View | DOI
 
2024 | Published | Conference Paper | IST-REx-ID: 18897 | OA
Improved convergence of score-based diffusion models via prediction-correction
F. Pedrotti, J. Maas, M. Mondelli, in:, Transactions on Machine Learning Research, 2024.
[Published Version] View | Files available | arXiv
 
2024 | Draft | Preprint | IST-REx-ID: 17350 | OA
Improved convergence of score-based diffusion models via prediction-correction
F. Pedrotti, J. Maas, M. Mondelli, ArXiv (n.d.).
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Thesis | IST-REx-ID: 17465 | OA
High-dimensional limits in artificial neural networks
A. Shevchenko, High-Dimensional Limits in Artificial Neural Networks, Institute of Science and Technology Austria, 2024.
[Published Version] View | Files available | DOI
 

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