Fathollahi D, Farsad N, Hashemi SA, Mondelli M. 2021. Sparse multi-decoder recursive projection aggregation for Reed-Muller codes. 2021 IEEE International Symposium on Information Theory. ISIT: International Symposium on Information Theory, 1082–1087.
LibreCat: https://research-explorer.ista.ac.at/record/10597
DOI: 10.1109/isit45174.2021.9517887
WoS: 000701502201029
arXiv: 2011.12882

Mondelli M, Venkataramanan R. 2021. PCA initialization for approximate message passing in rotationally invariant models. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 35, 29616–29629.
LibreCat: https://research-explorer.ista.ac.at/record/10593
arXiv: 2106.02356

Nguyen Q, Bréchet P, Mondelli M. 2021. When are solutions connected in deep networks? 35th Conference on Neural Information Processing Systems. 35th Conference on Neural Information Processing Systems vol. 35.
LibreCat: https://research-explorer.ista.ac.at/record/10594
arXiv: 2102.09671

Mondelli M, Venkataramanan R. 2021. Approximate message passing with spectral initialization for generalized linear models. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. AISTATS: Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, vol. 130, 397–405.
LibreCat: https://research-explorer.ista.ac.at/record/10598
arXiv: 2010.03460

Fazeli A, Hassani H, Mondelli M, Vardy A. 2021. Binary linear codes with optimal scaling: Polar codes with large kernels. IEEE Transactions on Information Theory. 67(9), 5693–5710.
LibreCat: https://research-explorer.ista.ac.at/record/9002
DOI: 10.1109/TIT.2020.3038806
arXiv: 1711.01339

Li S, Bitar R, Jaggi S, Zhang Y. 2021. Network coding with myopic adversaries. IEEE Journal on Selected Areas in Information Theory. 2(4), 1108–1119.
LibreCat: https://research-explorer.ista.ac.at/record/15254
DOI: 10.1109/JSAIT.2021.3126474
arXiv: 2102.09885

Nguyen Q, Mondelli M. 2020. Global convergence of deep networks with one wide layer followed by pyramidal topology. 34th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 33, 11961–11972.
LibreCat: https://research-explorer.ista.ac.at/record/9221
arXiv: 2002.07867

Mondelli M, Hashemi SA, Cioffi J, Goldsmith A. 2020. Simplified successive cancellation decoding of polar codes has sublinear latency. IEEE International Symposium on Information Theory - Proceedings. ISIT: Internation Symposium on Information Theory vol. 2020–June, 401–406.
LibreCat: https://research-explorer.ista.ac.at/record/8536
DOI: 10.1109/ISIT44484.2020.9174141
arXiv: 1909.04892

Shevchenko A, Mondelli M. 2020. Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks. Proceedings of the 37th International Conference on Machine Learning. vol. 119, 8773–8784.
LibreCat: https://research-explorer.ista.ac.at/record/9198
arXiv: 1912.10095

Javanmard A, Mondelli M, Montanari A. 2020. Analysis of a two-layer neural network via displacement convexity. Annals of Statistics. 48(6), 3619–3642.
LibreCat: https://research-explorer.ista.ac.at/record/6748
DOI: 10.1214/20-AOS1945
WoS: 000598369200021
arXiv: 1901.01375

Hashemi SA, Condo C, Mondelli M, Gross WJ. 2019. Rate-flexible fast polar decoders. IEEE Transactions on Signal Processing. 67(22), 8854897.
LibreCat: https://research-explorer.ista.ac.at/record/6750
DOI: 10.1109/TSP.2019.2944738
arXiv: 1903.09203

Mondelli M, Hassani SH, Urbanke R. 2019. A new coding paradigm for the primitive relay channel. Algorithms. 12(10), 218.
LibreCat: https://research-explorer.ista.ac.at/record/7007
DOI: 10.3390/a12100218
arXiv: 1801.03153