Andrea Montanari

 

Professor,
Department of Electrical Engineering,
Department of Statistics,
and (by courtesy) Department of Mathematics
Stanford University

Contact

Packard 272, Stanford, CA 94304
Tel: (650) 736-7422
Fax: (650) 723-8473
montanari@stanford.edu

Some representative papers

S. Mei, A. Montanari, The generalization error of random features regression: Precise asymptotics and double descent curve, 2019

B. Ghorbani, S. Mei, T. Misiakiewicz, A. Montanari Linearized two-layers neural networks in high dimension, 2019

A. Montanari, Optimization of the Serrington-Kirkpatrick Hamiltonian, 2019

Z. Fan, S. Mei, A. Montanari, TAP free energy, spin glasses, and variational inference, 2018

S. Mei, A. Montanari, P.-M. Nguyen, A Mean Field View of the Landscape of Two-Layers Neural Networks, 2018

E. Abbe, L. Massoulie, A. Montanari, A. Sly, N. Srivastava, Group Synchronization on Grids, 2017

H Javadi, A Montanari, Non-negative Matrix Factorization via Archetypal Analysis, 2017

S. Mei, Y. Bai and A. Montanari, The landscape of empirical risk for non-convex losses, 2017

A. Montanari and N. Sun, Spectral algorithms for tensor completion, 2016

A. Javanmard and A. Montanari, Online Rules for Control of False Discovery Rate and False Discovery Exceedance, 2015

A. Javanmard, A. Montanari, and F. Ricci-Tersenghi, Phase Transitions in Semidefinite Relaxations, (Including Supplementary Information), 2015 (code)

A. Montanari and S.Sen Semidefinite Programs on Sparse Random Graphs and their Application to Community Detection, 2015

A. Dembo, A. Montanari, S. Sen, Extremal Cuts of Sparse Random Graphs, 2015

A. Javanmard and A. Montanari, Confidence Intervals and Hypothesis Testing for High-Dimensional Regression, 2013 (code)

Y. Deshpande and A. Montanari, Finding Hidden Cliques of Size sqrt{N/e} in Nearly Linear Time, 2013

A. Montanari and A. Saberi, The Spread of Innovations in Social Networks, Proc. Natl. Acad. Sci., 2010 (conference version FOCS 2009)

D.L. Donoho, A. Maleki, and A. Montanari. Message passing algorithms for compressed sensing, Proc. Natl. Acad. Sci., 2009