Artigos com autorizações de acesso público - Andrea MontanariSaiba mais
2 artigos não disponíveis publicamente
An empirical scaling law for polar codes
SB Korada, A Montanari, E Telatar, R Urbanke
2010 IEEE International Symposium on Information Theory, 884-888, 2010
Autorizações: Swiss National Science Foundation
Mean field asymptotics in high-dimensional statistics: From exact results to efficient algorithms
A Montanari
Proceedings of the International Congress of Mathematicians: Rio de Janeiro …, 2018
Autorizações: US National Science Foundation
59 artigos disponíveis publicamente
A mean field view of the landscape of two-layer neural networks
S Mei, A Montanari, PM Nguyen
Proceedings of the National Academy of Sciences 115 (33), E7665-E7671, 2018
Autorizações: US National Science Foundation
Surprises in high-dimensional ridgeless least squares interpolation
T Hastie, A Montanari, S Rosset, RJ Tibshirani
Annals of statistics 50 (2), 949, 2022
Autorizações: US National Science Foundation, US Department of Defense, US National …
The generalization error of random features regression: Precise asymptotics and the double descent curve
S Mei, A Montanari
Communications on Pure and Applied Mathematics 75 (4), 667-766, 2022
Autorizações: US National Science Foundation, US Department of Defense
The landscape of empirical risk for nonconvex losses
S Mei, Y Bai, A Montanari
The Annals of Statistics 46 (6A), 2747-2774, 2018
Autorizações: US National Science Foundation
Deep learning: a statistical viewpoint
PL Bartlett, A Montanari, A Rakhlin
Acta numerica 30, 87-201, 2021
Autorizações: US National Science Foundation, US Department of Defense
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit
S Mei, T Misiakiewicz, A Montanari
Conference on learning theory, 2388-2464, 2019
Autorizações: US National Science Foundation, US Department of Defense
High dimensional robust m-estimation: Asymptotic variance via approximate message passing
D Donoho, A Montanari
Probability Theory and Related Fields 166, 935-969, 2016
Autorizações: US National Science Foundation
Linearized two-layers neural networks in high dimension
B Ghorbani, S Mei, T Misiakiewicz, A Montanari
Autorizações: US National Science Foundation, US Department of Defense
Debiasing the lasso: Optimal sample size for gaussian designs
A Javanmard, A Montanari
Autorizações: US National Science Foundation, US Department of Defense
When do neural networks outperform kernel methods?
B Ghorbani, S Mei, T Misiakiewicz, A Montanari
Advances in Neural Information Processing Systems 33, 14820-14830, 2020
Autorizações: US National Science Foundation, US Department of Defense
Asymptotic mutual information for the two-groups stochastic block model
Y Deshpande, E Abbe, A Montanari
Information and Inference, 2016, 2016
Autorizações: US National Science Foundation
State evolution for approximate message passing with non-separable functions
R Berthier, A Montanari, PM Nguyen
Information and Inference: A Journal of the IMA 9 (1), 33-79, 2020
Autorizações: US National Science Foundation
Semidefinite programs on sparse random graphs and their application to community detection
A Montanari, S Sen
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
Autorizações: US National Science Foundation
Contextual stochastic block models
Y Deshpande, S Sen, A Montanari, E Mossel
Advances in Neural Information Processing Systems 31, 2018
Autorizações: US National Science Foundation, US Department of Defense
Tight thresholds for cuckoo hashing via XORSAT
M Dietzfelbinger, A Goerdt, M Mitzenmacher, A Montanari, R Pagh, ...
Automata, Languages and Programming, 213-225, 2010
Autorizações: German Research Foundation
Optimization of the Sherrington--Kirkpatrick Hamiltonian
A Montanari
SIAM Journal on Computing, FOCS19-1-FOCS19-38, 2021
Autorizações: US National Science Foundation, US Department of Defense
Phase transitions in semidefinite relaxations
A Javanmard, A Montanari, F Ricci-Tersenghi
Proceedings of the National Academy of Sciences 113 (16), E2218-E2223, 2016
Autorizações: US National Science Foundation
Limitations of lazy training of two-layers neural network
B Ghorbani, S Mei, T Misiakiewicz, A Montanari
Advances in Neural Information Processing Systems 32, 2019
Autorizações: US National Science Foundation, US Department of Defense
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