Andrea Montanari

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 82

Top Venues

CoRR

COLT

NIPS

IEEE Trans. Inf. Theory

Publications

Andrea Montanari, Kangjie Zhou
Which exceptional low-dimensional projections of a Gaussian point cloud can be found in polynomial time? CoRR (2024)
Katherine L. Mentzer, Andrea Montanari
Scaling Training Data with Lossy Image Compression. CoRR (2024)
Andrea Montanari, Subhabrata Sen
A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists. Found. Trends Mach. Learn. 17 (1) (2024)
Ayush Jain, Andrea Montanari, Eren Sasoglu
Scaling laws for learning with real and surrogate data. CoRR (2024)
Katherine L. Mentzer, Andrea Montanari
Scaling Training Data with Lossy Image Compression. KDD (2024)
Andrea Montanari, Eliran Subag
On Smale's 17th problem over the reals. CoRR (2024)
Germain Kolossov, Andrea Montanari, Pulkit Tandon
Towards a statistical theory of data selection under weak supervision. ICLR (2024)
Andrea Montanari, Eric Weiner
Compressing Tabular Data via Latent Variable Estimation. CoRR (2023)
Theodor Misiakiewicz, Andrea Montanari
Six Lectures on Linearized Neural Networks. CoRR (2023)
Raphaël Berthier, Andrea Montanari, Kangjie Zhou
Learning time-scales in two-layers neural networks. CoRR (2023)
Andrea Montanari, Eric Weiner
Compressing Tabular Data via Latent Variable Estimation. ICML (2023)
Ahmed El Alaoui, Andrea Montanari, Mark Sellke
Local algorithms for maximum cut and minimum bisection on locally treelike regular graphs of large degree. Random Struct. Algorithms 63 (3) (2023)
Andrea Montanari
Sampling, Diffusions, and Stochastic Localization. CoRR (2023)
Germain Kolossov, Andrea Montanari, Pulkit Tandon
Towards a statistical theory of data selection under weak supervision. CoRR (2023)
Ahmed El Alaoui, Andrea Montanari, Mark Sellke
Sampling from the Sherrington-Kirkpatrick Gibbs measure via algorithmic stochastic localization. FOCS (2022)
Kangjie Zhou, Andrea Montanari
High-Dimensional Projection Pursuit: Outer Bounds and Applications to Interpolation in Neural Networks. COLT (2022)
Ahmed El Alaoui, Andrea Montanari, Mark Sellke
Sampling from the Sherrington-Kirkpatrick Gibbs measure via algorithmic stochastic localization. CoRR (2022)
Andrea Montanari, Yuchen Wu
Adversarial Examples in Random Neural Networks with General Activations. CoRR (2022)
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23 (2022)
Andrea Montanari, Basil Saeed
Universality of empirical risk minimization. COLT (2022)
Andrea Montanari, Basil Saeed
Universality of empirical risk minimization. CoRR (2022)
Ahmed El Alaoui, Andrea Montanari
An Information-Theoretic View of Stochastic Localization. IEEE Trans. Inf. Theory 68 (11) (2022)
Andrea Montanari, Kangjie Zhou
Overparametrized linear dimensionality reductions: From projection pursuit to two-layer neural networks. CoRR (2022)
Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
Deep learning: a statistical viewpoint. CoRR (2021)
Ahmed El Alaoui, Andrea Montanari, Mark Sellke
Local algorithms for Maximum Cut and Minimum Bisection on locally treelike regular graphs of large degree. CoRR (2021)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Learning with invariances in random features and kernel models. COLT (2021)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Learning with invariances in random features and kernel models. CoRR (2021)
Andrea Montanari, Yiqiao Zhong, Kangjie Zhou
Tractability from overparametrization: The example of the negative perceptron. CoRR (2021)
Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
Deep learning: a statistical viewpoint. Acta Numer. 30 (2021)
Ahmed El Alaoui, Andrea Montanari
An Information-Theoretic View of Stochastic Localization. CoRR (2021)
Yuchen Wu, MohammadHossein Bateni, André Linhares, Filipe Miguel Gonçalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard, Jakab Tardos
Streaming Belief Propagation for Community Detection. CoRR (2021)
Yuchen Wu, Jakab Tardos, MohammadHossein Bateni, André Linhares, Filipe Miguel Gonçalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard
Streaming Belief Propagation for Community Detection. NeurIPS (2021)
Michael Celentano, Theodor Misiakiewicz, Andrea Montanari
Minimum complexity interpolation in random features models. CoRR (2021)
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR (2020)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
When Do Neural Networks Outperform Kernel Methods? NeurIPS (2020)
Andrea Montanari, Yiqiao Zhong
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training. CoRR (2020)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
When Do Neural Networks Outperform Kernel Methods? CoRR (2020)
Michael Celentano, Andrea Montanari, Yuting Wei
The Lasso with general Gaussian designs with applications to hypothesis testing. CoRR (2020)
Michael Celentano, Andrea Montanari, Yuchen Wu
The estimation error of general first order methods. COLT (2020)
Michael Celentano, Andrea Montanari, Yuchen Wu
The estimation error of general first order methods. CoRR (2020)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. CoRR (2019)
Yash Deshpande, Andrea Montanari, Ryan O'Donnell, Tselil Schramm, Subhabrata Sen
The threshold for SDP-refutation of random regular NAE-3SAT. SODA (2019)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
Linearized two-layers neural networks in high dimension. CoRR (2019)
Marco Mondelli, Andrea Montanari
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition. AISTATS (2019)
Adel Javanmard, Marco Mondelli, Andrea Montanari
Analysis of a Two-Layer Neural Network via Displacement Convexity. CoRR (2019)
Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani
Surprises in High-Dimensional Ridgeless Least Squares Interpolation. CoRR (2019)
Marco Mondelli, Andrea Montanari
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval. Found. Comput. Math. 19 (3) (2019)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. COLT (2019)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
Limitations of Lazy Training of Two-layers Neural Network. NeurIPS (2019)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
Limitations of Lazy Training of Two-layers Neural Networks. CoRR (2019)
Behrooz Ghorbani, Hamid Javadi, Andrea Montanari
An Instability in Variational Inference for Topic Models. ICML (2019)
Ahmed El Alaoui, Andrea Montanari
On the computational tractability of statistical estimation on amenable graphs. CoRR (2019)
Andrea Montanari
Optimization of the Sherrington-Kirkpatrick Hamiltonian. FOCS (2019)
Andrea Montanari, Feng Ruan, Jun Yan
Adapting to Unknown Noise Distribution in Matrix Denoising. CoRR (2018)
Yash Deshpande, Andrea Montanari, Elchanan Mossel, Subhabrata Sen
Contextual Stochastic Block Models. CoRR (2018)
Hamid Javadi, Andrea Montanari
A Statistical Model for Motifs Detection. IEEE Trans. Inf. Theory 64 (12) (2018)
Yash Deshpande, Subhabrata Sen, Andrea Montanari, Elchanan Mossel
Contextual Stochastic Block Models. NeurIPS (2018)
Song Mei, Andrea Montanari, Phan-Minh Nguyen
A Mean Field View of the Landscape of Two-Layers Neural Networks. CoRR (2018)
Marco Mondelli, Andrea Montanari
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval. COLT (2018)
Yash Deshpande, Andrea Montanari, Ryan O'Donnell, Tselil Schramm, Subhabrata Sen
The threshold for SDP-refutation of random regular NAE-3SAT. CoRR (2018)
Mohsen Bayati, Andrea Montanari, Amin Saberi
Generating Random Networks Without Short Cycles. Oper. Res. 66 (5) (2018)
Marco Mondelli, Andrea Montanari
On the Connection Between Learning Two-Layers Neural Networks and Tensor Decomposition. CoRR (2018)
Murat A. Erdogdu, Yash Deshpande, Andrea Montanari
Inference in Graphical Models via Semidefinite Programming Hierarchies. NIPS (2017)
Marco Mondelli, Andrea Montanari
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval. CoRR (2017)
Andrea Montanari, Phan-Minh Nguyen
Universality of the elastic net error. ISIT (2017)
Andrea Montanari, Daniel Reichman, Ofer Zeitouni
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank One Perturbations of Gaussian Tensors. IEEE Trans. Inf. Theory 63 (3) (2017)
Hamid Javadi, Andrea Montanari
Non-negative Matrix Factorization via Archetypal Analysis. CoRR (2017)
Raphaël Berthier, Andrea Montanari, Phan-Minh Nguyen
State Evolution for Approximate Message Passing with Non-Separable Functions. CoRR (2017)
Zhou Fan, Andrea Montanari
How well do local algorithms solve semidefinite programs? STOC (2017)
Song Mei, Theodor Misiakiewicz, Andrea Montanari, Roberto Imbuzeiro Oliveira
Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality. COLT (2017)
Emmanuel Abbe, Laurent Massoulié, Andrea Montanari, Allan Sly, Nikhil Srivastava
Group Synchronization on Grids. CoRR (2017)
Murat A. Erdogdu, Yash Deshpande, Andrea Montanari
Inference in Graphical Models via Semidefinite Programming Hierarchies. CoRR (2017)
Stratis Ioannidis, Andrea Montanari
Learning Combinations of Sigmoids Through Gradient Estimation. CoRR (2017)
Yash Deshpande, Emmanuel Abbe, Andrea Montanari
Asymptotic mutual information for the binary stochastic block model. ISIT (2016)
Andrea Montanari, Nike Sun
Spectral algorithms for tensor completion. CoRR (2016)
Andrea Montanari, Emile Richard
Non-Negative Principal Component Analysis: Message Passing Algorithms and Sharp Asymptotics. IEEE Trans. Inf. Theory 62 (3) (2016)
Adel Javanmard, Andrea Montanari, Federico Ricci-Tersenghi
Performance of a community detection algorithm based on semidefinite programming. CoRR (2016)
Adel Javanmard, Andrea Montanari
Online Rules for Control of False Discovery Rate and False Discovery Exceedance. CoRR (2016)
Zhou Fan, Andrea Montanari
How Well Do Local Algorithms Solve Semidefinite Programs? CoRR (2016)
Andrea Montanari, Subhabrata Sen
Semidefinite programs on sparse random graphs and their application to community detection. STOC (2016)
Andrea Montanari
Effective compression maps for torus-based cryptography. Des. Codes Cryptogr. 79 (1) (2016)
Yash Deshpande, Andrea Montanari
Sparse PCA via Covariance Thresholding. J. Mach. Learn. Res. 17 (2016)
Yash Deshpande, Andrea Montanari
Finding Hidden Cliques of Size √(N/e) in Nearly Linear Time. Found. Comput. Math. 15 (4) (2015)
Andrea Montanari, Subhabrata Sen
Semidefinite Programs on Sparse Random Graphs. CoRR (2015)
Adel Javanmard, Andrea Montanari, Federico Ricci-Tersenghi
Phase Transitions in Semidefinite Relaxations. CoRR (2015)
Hamid Haj Seyed Javadi, Andrea Montanari
The Hidden Subgraph Problem. CoRR (2015)
Andrea Montanari, Daniel Reichman, Ofer Zeitouni
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors. NIPS (2015)
Mohsen Bayati, Sonia Bhaskar, Andrea Montanari
A Low-Cost Method for Multiple Disease Prediction. AMIA (2015)
Yash Deshpande, Emmanuel Abbe, Andrea Montanari
Asymptotic Mutual Information for the Two-Groups Stochastic Block Model. CoRR (2015)
Jeffrey G. Andrews, Alexandros G. Dimakis, Lara Dolecek, Michelle Effros, Muriel Médard, Olgica Milenkovic, Andrea Montanari, Sriram Vishwanath, Edmund M. Yeh, Randall Berry, Ken R. Duffy, Soheil Feizi, Saul Kato, Manolis Kellis, Stuart Licht, Jon Sorenson, Lav R. Varshney, Haris Vikalo
A Perspective on Future Research Directions in Information Theory. CoRR (2015)
Adel Javanmard, Andrea Montanari
On Online Control of False Discovery Rate. CoRR (2015)
Murat A. Erdogdu, Andrea Montanari
Convergence rates of sub-sampled Newton methods. NIPS (2015)
Murat A. Erdogdu, Nadia Fawaz, Andrea Montanari
Privacy-Utility Trade-Off for Time-Series with Application to Smart-Meter Data. AAAI Workshop: Computational Sustainability (2015)
Amir Dembo, Andrea Montanari, Subhabrata Sen
Extremal Cuts of Sparse Random Graphs. CoRR (2015)
Emmanuel Abbe, Andrea Montanari
Conditional Random Fields, Planted Constraint Satisfaction, and Entropy Concentration. Theory Comput. 11 (2015)
Andrea Montanari
Finding One Community in a Sparse Graph. CoRR (2015)
Yash Deshpande, Andrea Montanari
Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems. COLT (2015)
Mohsen Bayati, Christian Borgs, Jennifer T. Chayes, Yash Kanoria, Andrea Montanari
Bargaining dynamics in exchange networks. J. Econ. Theory 156 (2015)
Yash Deshpande, Andrea Montanari
Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems. CoRR (2015)
Eric W. Tramel, Santhosh Kumar, Andrei Giurgiu, Andrea Montanari
Statistical Estimation: From Denoising to Sparse Regression and Hidden Cliques. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Andrea Montanari