Prix Lopez-Loretta 2019 - Marco Mondelli

Project Period: 2020-10-01 – 2025-09-30
Externally Funded
Principal Investigator
Marco Mondelli
Department(s)
Mondelli Group
Funding Organisation
Fondation_Lopez_Loreta

13 Publications

2021 | Conference Paper | IST-REx-ID: 10593 | OA
PCA initialization for approximate message passing in rotationally invariant models
M. Mondelli, R. Venkataramanan, in:, 35th Conference on Neural Information Processing Systems, NeurIPS, n.d.
View | Download Preprint (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10594 | OA
When are solutions connected in deep networks?
Q. Nguyen, P. Bréchet, M. Mondelli, in:, 35th Conference on Neural Information Processing Systems, NeurIPS, n.d.
View | Download Preprint (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10595 | OA
Tight bounds on the smallest eigenvalue of the neural tangent kernel for deep ReLU networks
Q. Nguyen, M. Mondelli, G.F. Montufar, in:, M. Meila, T. Zhang (Eds.), Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 8119–8129.
View | Download Published Version (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10597 | OA
Sparse multi-decoder recursive projection aggregation for Reed-Muller codes
D. Fathollahi, N. Farsad, S.A. Hashemi, M. Mondelli, in:, 2021 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2021, pp. 1082–1087.
View | DOI | Download Preprint (ext.) | arXiv
 
2022 | Conference Paper | IST-REx-ID: 10599 | OA
Successive syndrome-check decoding of polar codes
S.A. Hashemi, M. Mondelli, J. Cioffi, A. Goldsmith, in:, Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, IEEE Signal Processing Society, 2022, pp. 943–947.
View | DOI | Download Preprint (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9198 | OA
Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks
A. Shevchenko, M. Mondelli, in:, Proceedings of the 37th International Conference on Machine Learning, Proceedings of Machine Learning Research, 2020, pp. 8773–8784.
View | Files available | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9221 | OA
Global convergence of deep networks with one wide layer followed by pyramidal topology
Q. Nguyen, M. Mondelli, in:, 34th Conference on Neural Information Processing Systems, Curran Associates, 2020, pp. 11961–11972.
View | Download Preprint (ext.) | arXiv
 
2022 | Journal Article | IST-REx-ID: 11420 | OA
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.
View | Files available | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10053 | OA
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.
View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2022 | Journal Article | IST-REx-ID: 10364 | OA
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.
View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2022 | Conference Paper | IST-REx-ID: 12016 | OA
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.
View | DOI | Download Preprint (ext.) | arXiv
 
2022 | Journal Article | IST-REx-ID: 12480 | OA
Approximate message passing with spectral initialization for generalized linear models
M. Mondelli, R. Venkataramanan, Journal of Statistical Mechanics: Theory and Experiment 2022 (2022).
View | Files available | DOI
 
2021 | Conference Paper | IST-REx-ID: 10598 | OA
Approximate message passing with spectral initialization for generalized linear models
Mondelli, Marco, Approximate message passing with spectral initialization for generalized linear models. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics 130. 2021
View | Files available | Download Preprint (ext.) | arXiv