Prix Lopez-Loretta 2019 - Marco Mondelli
Project Period: 2020-10-01 – 2025-09-30
Funder:
Fondation_Lopez_Loreta
Principal Investigator
Department(s)
Funder
Fondation_Lopez_Loreta
28 Publications
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.
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A. Depope, M. Mondelli, M.R. Robinson, in:, 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, 2024, pp. 13151–13155.
2024 | Submitted | Preprint | IST-REx-ID: 17350 |
Improved convergence of score-based diffusion models via prediction-correction
F. Pedrotti, J. Maas, M. Mondelli, ArXiv (n.d.).
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F. Pedrotti, J. Maas, M. Mondelli, ArXiv (n.d.).
2024 | Published | Thesis | IST-REx-ID: 17465 |
High-dimensional limits in artificial neural networks
A. Shevchenko, High-Dimensional Limits in Artificial Neural Networks, Institute of Science and Technology Austria, 2024.
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A. Shevchenko, High-Dimensional Limits in Artificial Neural Networks, Institute of Science and Technology Austria, 2024.
2024 | Published | Conference Paper | IST-REx-ID: 17469 |
Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth
K. Kögler, A. Shevchenko, H. Hassani, M. Mondelli, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 24964–25015.
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K. Kögler, A. Shevchenko, H. Hassani, M. Mondelli, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 24964–25015.
2024 | Published | Journal Article | IST-REx-ID: 15172 |
Concentration without independence via information measures
A.R. Esposito, M. Mondelli, IEEE Transactions on Information Theory 70 (2024) 3823–3839.
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A.R. Esposito, M. Mondelli, IEEE Transactions on Information Theory 70 (2024) 3823–3839.
2023 | Published | Journal Article | IST-REx-ID: 13315 |
Fundamental limits in structured principal component analysis and how to reach them
J. Barbier, F. Camilli, M. Mondelli, M. Sáenz, Proceedings of the National Academy of Sciences of the United States of America 120 (2023).
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J. Barbier, F. Camilli, M. Mondelli, M. Sáenz, Proceedings of the National Academy of Sciences of the United States of America 120 (2023).
2023 | Published | Conference Paper | IST-REx-ID: 13321 |
Approximate message passing for multi-layer estimation in rotationally invariant models
Y. Xu, T.Q. Hou, S.S. Liang, M. Mondelli, in:, 2023 IEEE Information Theory Workshop, Institute of Electrical and Electronics Engineers, 2023, pp. 294–298.
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Y. Xu, T.Q. Hou, S.S. Liang, M. Mondelli, in:, 2023 IEEE Information Theory Workshop, Institute of Electrical and Electronics Engineers, 2023, pp. 294–298.
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Fundamental limits of two-layer autoencoders, and achieving them with gradient methods
A. Shevchenko, K. Kögler, H. Hassani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 31151–31209.
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A. Shevchenko, K. Kögler, H. Hassani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 31151–31209.
2023 | Published | Conference Paper | IST-REx-ID: 12859 |
Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels
S. Bombari, S. Kiyani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 2738–2776.
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S. Bombari, S. Kiyani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 2738–2776.
2023 | Published | Conference Paper | IST-REx-ID: 14921 |
Deep neural collapse is provably optimal for the deep unconstrained features model
P. Súkeník, M. Mondelli, C. Lampert, in:, 37th Annual Conference on Neural Information Processing Systems, 2023.
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P. Súkeník, M. Mondelli, C. Lampert, in:, 37th Annual Conference on Neural Information Processing Systems, 2023.
2023 | Published | Conference Paper | IST-REx-ID: 14922 |
Concentration without independence via information measures
A.R. Esposito, M. Mondelli, in:, Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, 2023, pp. 400–405.
[Preprint]
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A.R. Esposito, M. Mondelli, in:, Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, 2023, pp. 400–405.
2023 | Published | Conference Paper | IST-REx-ID: 14924 |
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence
D. Wu, V. Kungurtsev, M. Mondelli, in:, Transactions on Machine Learning Research, ML Research Press, 2023.
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D. Wu, V. Kungurtsev, M. Mondelli, in:, Transactions on Machine Learning Research, ML Research Press, 2023.
2022 | Published | Journal Article | IST-REx-ID: 10364 |
Parallelism versus latency in simplified successive-cancellation decoding of polar codes
S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, IEEE Transactions on Wireless Communications 21 (2022) 3909–3920.
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S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, IEEE Transactions on Wireless Communications 21 (2022) 3909–3920.
2022 | Published | Journal Article | IST-REx-ID: 11420 |
Mean-field analysis of piecewise linear solutions for wide ReLU networks
A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.
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A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.
2022 | Published | Conference Paper | IST-REx-ID: 12016 |
Polar coded computing: The role of the scaling exponent
D. Fathollahi, M. Mondelli, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2154–2159.
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D. Fathollahi, M. Mondelli, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2154–2159.
2022 | Published | Journal Article | IST-REx-ID: 12480 |
Approximate message passing with spectral initialization for generalized linear models
M. Mondelli, R. Venkataramanan, Journal of Statistical Mechanics: Theory and Experiment 2022 (2022).
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M. Mondelli, R. Venkataramanan, Journal of Statistical Mechanics: Theory and Experiment 2022 (2022).
2022 | Published | Conference Paper | IST-REx-ID: 12537 |
Memorization and optimization in deep neural networks with minimum over-parameterization
S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information Processing Systems, Curran Associates, 2022, pp. 7628–7640.
[Preprint]
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S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information Processing Systems, Curran Associates, 2022, pp. 7628–7640.
2022 | Published | Conference Paper | IST-REx-ID: 12540 |
Estimation in rotationally invariant generalized linear models via approximate message passing
R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022.
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R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022.
2021 | Published | Conference Paper | IST-REx-ID: 10053 |
Parallelism versus latency in simplified successive-cancellation decoding of polar codes
S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, in:, 2021 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2021, pp. 2369–2374.
[Preprint]
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S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, in:, 2021 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2021, pp. 2369–2374.
2021 | Published | Conference Paper | IST-REx-ID: 10593 |
PCA initialization for approximate message passing in rotationally invariant models
M. Mondelli, R. Venkataramanan, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 29616–29629.
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M. Mondelli, R. Venkataramanan, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 29616–29629.