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Marco Mondelli
Marco Mondelli
Assistant Professor, IST Austria
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Reed-Muller codes achieve capacity on erasure channels
S Kudekar, S Kumar, M Mondelli, HD Pfister, E Şaşoğlu, R Urbanke
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
171*2016
Unified scaling of polar codes: Error exponent, scaling exponent, moderate deviations, and error floors
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Information Theory 62 (12), 6698-6712, 2016
1282016
From polar to Reed-Muller codes: A technique to improve the finite-length performance
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Communications 62 (9), 3084-3091, 2014
1182014
Fundamental limits of weak recovery with applications to phase retrieval
M Mondelli, A Montanari
Conference On Learning Theory, 1445-1450, 2018
982018
How to achieve the capacity of asymmetric channels
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Information Theory 64 (5), 3371-3393, 2018
90*2018
Achieving Marton’s region for broadcast channels using polar codes
M Mondelli, SH Hassani, I Sason, RL Urbanke
IEEE Transactions on Information Theory 61 (2), 783-800, 2014
882014
On the decoding of polar codes on permuted factor graphs
N Doan, SA Hashemi, M Mondelli, WJ Gross
2018 IEEE Global Communications Conference (GLOBECOM), 1-6, 2018
692018
Construction of polar codes with sublinear complexity
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Information Theory 65 (5), 2782-2791, 2018
582018
Binary linear codes with optimal scaling: Polar codes with large kernels
A Fazeli, H Hassani, M Mondelli, A Vardy
IEEE Transactions on Information Theory 67 (9), 5693-5710, 2020
53*2020
Analysis of a two-layer neural network via displacement convexity
A Javanmard, M Mondelli, A Montanari
The Annals of Statistics 48 (6), 3619-3642, 2020
502020
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition
M Mondelli, A Montanari
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2019
502019
Decoder partitioning: Towards practical list decoding of polar codes
SA Hashemi, M Mondelli, SH Hassani, C Condo, RL Urbanke, WJ Gross
IEEE Transactions on Communications 66 (9), 3749-3759, 2018
472018
Scaling exponent of list decoders with applications to polar codes
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Information Theory 61 (9), 4838-4851, 2015
472015
Decoding Reed-Muller and polar codes by successive factor graph permutations
SA Hashemi, N Doan, M Mondelli, WJ Gross
2018 IEEE 10th International Symposium on Turbo Codes & Iterative …, 2018
462018
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology
Q Nguyen, M Mondelli
Advances in Neural Information Processing Systems (NeurIPS), 2020, 2020
342020
Partitioned list decoding of polar codes: Analysis and improvement of finite length performance
SA Hashemi, M Mondelli, SH Hassani, R Urbanke, WJ Gross
GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-7, 2017
272017
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Q Nguyen, M Mondelli, G Montufar
International Conference on Machine Learning (ICML), 2021, 2021
252021
Comparing the bit-MAP and block-MAP decoding thresholds of Reed-Muller codes on BMS channels
S Kudekar, S Kumar, M Mondelli, HD Pfister, R Urbankez
2016 IEEE International Symposium on Information Theory (ISIT), 1755-1759, 2016
242016
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
A Shevchenko, M Mondelli
International Conference on Machine Learning (ICML), 2020, 2020
232020
Sparse Multi-Decoder Recursive Projection Aggregation for Reed-Muller Codes
D Fathollahi, N Farsad, SA Hashemi, M Mondelli
IEEE International Symposium on Information Theory (ISIT), 2021, 2021
172021
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Artiklar 1–20