Marco Mondelli
Orcid: 0000-0002-3242-7020
According to our database1,
Marco Mondelli
authored at least 67 papers
between 2011 and 2024.
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Bibliography
2024
Contraction of Markovian Operators in Orlicz Spaces and Error Bounds for Markov Chain Monte Carlo.
CoRR, 2024
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth.
CoRR, 2024
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features.
CoRR, 2024
2023
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence.
Trans. Mach. Learn. Res., 2023
Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing.
CoRR, 2023
CoRR, 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models.
Proceedings of the IEEE Information Theory Workshop, 2023
Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise.
Proceedings of the IEEE International Symposium on Information Theory, 2023
Proceedings of the IEEE International Symposium on Information Theory, 2023
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods.
Proceedings of the International Conference on Machine Learning, 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels.
Proceedings of the International Conference on Machine Learning, 2023
2022
Parallelism Versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes.
IEEE Trans. Wirel. Commun., 2022
IEEE Trans. Commun., 2022
J. Mach. Learn. Res., 2022
Found. Comput. Math., 2022
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods.
CoRR, 2022
CoRR, 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the IEEE Information Theory Workshop, 2022
Proceedings of the IEEE International Symposium on Information Theory, 2022
Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.
Proceedings of the International Conference on Machine Learning, 2022
2021
IEEE Trans. Wirel. Commun., 2021
IEEE Trans. Inf. Theory, 2021
On Connectivity of Solutions in Deep Learning: The Role of Over-parameterization and Feature Quality.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the IEEE International Symposium on Information Theory, 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021
Approximate Message Passing with Spectral Initialization for Generalized Linear Models.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
2020
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the IEEE International Symposium on Information Theory, 2020
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Found. Comput. Math., 2019
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
IEEE Trans. Commun., 2018
On the Connection Between Learning Two-Layers Neural Networks and Tensor Decomposition.
CoRR, 2018
Proceedings of the 10th IEEE International Symposium on Turbo Codes & Iterative Information Processing, 2018
Proceedings of the IEEE Global Communications Conference, 2018
2017
IEEE Trans. Inf. Theory, 2017
Proceedings of the 2017 IEEE Wireless Communications and Networking Conference Workshops, 2017
Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance.
Proceedings of the 2017 IEEE Global Communications Conference, 2017
2016
From Polar to Reed-Muller Codes - Unified Scaling, Non-standard Channels, and a Proven Conjecture.
PhD thesis, 2016
Unified Scaling of Polar Codes: Error Exponent, Scaling Exponent, Moderate Deviations, and Error Floors.
IEEE Trans. Inf. Theory, 2016
Comparing the bit-MAP and block-MAP decoding thresholds of reed-muller codes on BMS channels.
Proceedings of the IEEE International Symposium on Information Theory, 2016
2015
IEEE Trans. Inf. Theory, 2015
IEEE Trans. Inf. Theory, 2015
CoRR, 2015
2014
Joint Power Allocation and Path Selection for Multi-Hop Noncoherent Decode and Forward UWB Communications.
IEEE Trans. Wirel. Commun., 2014
From Polar to Reed-Muller Codes: A Technique to Improve the Finite-Length Performance.
IEEE Trans. Commun., 2014
Achieving the Superposition and Binning Regions for Broadcast Channels Using Polar Codes.
CoRR, 2014
2013
Image Process. Line, 2013
2012
A cooperative approach for amplify-and-forward differential transmitted reference IR-UWB relay systems.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012
2011