Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).

We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.




71 Publications

2021 | Published | 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.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | 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, Institute of Electrical and Electronics Engineers, 2021, pp. 943–947.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | 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.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 13146 | OA
Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks
Nguyen, Quynh, Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks. Proceedings of the 38th International Conference on Machine Learning 139. 2021
[Published Version] View | Files available | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10598 | OA
Approximate message passing with spectral initialization for generalized linear models
M. Mondelli, R. Venkataramanan, in:, A. Banerjee, K. Fukumizu (Eds.), Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2021, pp. 397–405.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2020 | Published | Journal Article | IST-REx-ID: 6748 | OA
Analysis of a two-layer neural network via displacement convexity
A. Javanmard, M. Mondelli, A. Montanari, Annals of Statistics 48 (2020) 3619–3642.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 8536 | OA
Simplified successive cancellation decoding of polar codes has sublinear latency
Mondelli, Marco, Simplified successive cancellation decoding of polar codes has sublinear latency. IEEE International Symposium on Information Theory - Proceedings 2020-June. 2020
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 9221 | OA
Global convergence of deep networks with one wide layer followed by pyramidal topology
Nguyen, Quynh, Global convergence of deep networks with one wide layer followed by pyramidal topology. 34th Conference on Neural Information Processing Systems 33. 2020
[Preprint] View | Download Preprint (ext.) | arXiv
 
2020 | Published | 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, ML Research Press, 2020, pp. 8773–8784.
[Published Version] View | Files available | arXiv
 
2019 | Published | Journal Article | IST-REx-ID: 7007 | OA
A new coding paradigm for the primitive relay channel
M. Mondelli, S.H. Hassani, R. Urbanke, Algorithms 12 (2019).
[Published Version] View | Files available | DOI | arXiv
 
2019 | Published | Journal Article | IST-REx-ID: 6750 | OA
Rate-flexible fast polar decoders
S.A. Hashemi, C. Condo, M. Mondelli, W.J. Gross, IEEE Transactions on Signal Processing 67 (2019).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

Search

Filter Publications

Display / Sort

Citation Style: Default

Export / Embed