Andrea Montanari

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Adel JavanmardAssociate Professor, University of Southern CaliforniaAdresse e-mail validée de usc.edu
Ruediger UrbankeEPFLAdresse e-mail validée de epfl.ch
Song MeiAssistant Professor at UC BerkeleyAdresse e-mail validée de berkeley.edu
Mohsen BayatiProfessor, Stanford UniversityAdresse e-mail validée de stanford.edu
Sewoong OhPaul G. Allen School of Computer Science and Engineering, University of WashingtonAdresse e-mail validée de cs.washington.edu
Arian MalekiColumbia UniversityAdresse e-mail validée de stat.columbia.edu
Federico Ricci-TersenghiProfessor of Theoretical Physics, "La Sapienza" University, RomaAdresse e-mail validée de roma1.infn.it
Marc MezardBocconi University MilanoAdresse e-mail validée de unibocconi.it
Yash DeshpandeMember of Research Staff, Voleon (Typical Set, LLC)Adresse e-mail validée de mit.edu
Raghunandan KeshavanElectrical Engineering, Stanford UniveristyAdresse e-mail validée de stanford.edu
Theodor MisiakiewiczGraduate student, Stanford UniversityAdresse e-mail validée de stanford.edu
Guilhem SemerjianLPT-ENSAdresse e-mail validée de lpt.ens.fr
"Yashodhan Kanoria" OR "Yash Kanor...Columbia Business SchoolAdresse e-mail validée de columbia.edu
Amin SaberiProfessor, Stanford UniversityAdresse e-mail validée de stanford.edu
amir demboprofessor of mathematics and statistics, stanford universityAdresse e-mail validée de stat.stanford.edu
Phan-Minh NguyenThe Voleon GroupAdresse e-mail validée de alumni.stanford.edu
Abdelaziz AmraouiAdresse e-mail validée de theaagroup.ch
Behrooz GhorbaniResearcher, OpenAIAdresse e-mail validée de stanford.edu
Balaji PrabhakarAdresse e-mail validée de stanford.edu
Stratis IoannidisNortheastern UniversityAdresse e-mail validée de neu.edu

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Andrea Montanari

Professor of Statistics and Mathematics, Stanford University

Adresse e-mail validée de stanford.edu - Page d'accueil

statistics machine learning probability theory information theory signal processing


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Message-passing algorithms for compressed sensing DL Donoho, A Maleki, A Montanari Proceedings of the National Academy of Sciences 106 (45), 18914-18919, 2009	2375	2009
Information, physics, and computation M Mezard, A Montanari Oxford University Press, USA, 2009	2245	2009
Matrix completion from a few entries RH Keshavan, A Montanari, S Oh Information Theory, IEEE Transactions on 56 (6), 2980-2998, 2010	1460	2010
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	1060	2011
Confidence intervals and hypothesis testing for high-dimensional regression A Javanmard, A Montanari The Journal of Machine Learning Research 15 (1), 2869-2909, 2014	943	2014
Matrix completion from noisy entries RH Keshavan, A Montanari, S Oh The Journal of Machine Learning Research 11, 2057-2078, 2010	855	2010
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	688	2018
Surprises in high-dimensional ridgeless least squares interpolation T Hastie, A Montanari, S Rosset, RJ Tibshirani Annals of statistics 50 (2), 949, 2022	644	2022
Underspecification presents challenges for credibility in modern machine learning A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... The Journal of Machine Learning Research 23 (1), 10237-10297, 2022	536	2022
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	518	2010
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	512	2007
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	466	2022
The spread of innovations in social networks A Montanari, A Saberi Proceedings of the National Academy of Sciences 107 (47), 20196-20201, 2010	459	2010
The LASSO risk for Gaussian matrices M Bayati, A Montanari IEEE Transactions on Information Theory 58 (4), 1997-2017, 2011	324	2011
The landscape of empirical risk for nonconvex losses S Mei, Y Bai, A Montanari The Annals of Statistics 46 (6A), 2747-2774, 2018	308	2018
The noise-sensitivity phase transition in compressed sensing DL Donoho, A Maleki, A Montanari IEEE Transactions on Information Theory 57 (10), 6920-6941, 2011	306	2011
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	297	2013
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	280	2008
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	263	2013
A statistical model for tensor PCA A Montanari, E Richard Advances in Neural Information Processing Systems, 2897-2905, 2014	254*	2014

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