Követés
Andrea Montanari
Andrea Montanari
Professor of Electrical Engineering and Statistics, Stanford University
E-mail megerősítve itt: stanford.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Message-passing algorithms for compressed sensing
DL Donoho, A Maleki, A Montanari
Proceedings of the National Academy of Sciences 106 (45), 18914-18919, 2009
22542009
Information, physics, and computation
M Mezard, A Montanari
Oxford University Press, USA, 2009
21142009
Matrix completion from a few entries
RH Keshavan, A Montanari, S Oh
Information Theory, IEEE Transactions on 56 (6), 2980-2998, 2010
14222010
The dynamics of message passing on dense graphs, with applications to compressed sensing
M Bayati, A Montanari
Information Theory, IEEE Transactions on 57 (2), 764-785, 2011
9972011
Confidence intervals and hypothesis testing for high-dimensional regression
A Javanmard, A Montanari
The Journal of Machine Learning Research 15 (1), 2869-2909, 2014
8782014
Matrix completion from noisy entries
RH Keshavan, A Montanari, S Oh
The Journal of Machine Learning Research 11, 2057-2078, 2010
8212010
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
6062018
Surprises in high-dimensional ridgeless least squares interpolation
T Hastie, A Montanari, S Rosset, RJ Tibshirani
The Annals of Statistics 50 (2), 949-986, 2022
5422022
Gibbs states and the set of solutions of random constraint satisfaction problems
F Krzakała, A Montanari, F Ricci-Tersenghi, G Semerjian, L Zdeborová
Proceedings of the National Academy of Sciences 104 (25), 10318, 2007
4932007
Message passing algorithms for compressed sensing: I. motivation and construction
DL Donoho, A Maleki, A Montanari
2010 IEEE information theory workshop on information theory (ITW 2010, Cairo …, 2010
4862010
The spread of innovations in social networks
A Montanari, A Saberi
Proceedings of the National Academy of Sciences 107 (47), 20196-20201, 2010
4432010
Underspecification presents challenges for credibility in modern machine learning
A D’Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research, 2020
4272020
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
3992022
The LASSO risk for Gaussian matrices
M Bayati, A Montanari
IEEE Transactions on Information Theory 58 (4), 1997-2017, 2011
3032011
The noise-sensitivity phase transition in compressed sensing
DL Donoho, A Maleki, A Montanari
IEEE Transactions on Information Theory 57 (10), 6920-6941, 2011
2982011
The landscape of empirical risk for nonconvex losses
S Mei, Y Bai, A Montanari
The Annals of Statistics 46 (6A), 2747-2774, 2018
2842018
Information-theoretically optimal compressed sensing via spatial coupling and approximate message passing
DL Donoho, A Javanmard, A Montanari
Information Theory, IEEE Transactions on 59 (11), 7434-7464, 2013
2782013
Counter braids: a novel counter architecture for per-flow measurement
Y Lu, A Montanari, B Prabhakar, S Dharmapurikar, A Kabbani
ACM SIGMETRICS Performance Evaluation Review 36 (1), 121-132, 2008
2782008
State evolution for general approximate message passing algorithms, with applications to spatial coupling
A Javanmard, A Montanari
Information and Inference: A Journal of the IMA 2 (2), 115-144, 2013
2382013
Graphical models concepts in compressed sensing.
A Montanari, YC Eldar, G Kutyniok
Compressed Sensing, 394-438, 2012
2332012
A rendszer jelenleg nem tudja elvégezni a műveletet. Próbálkozzon újra később.
Cikkek 1–20