Montanari, Andrea

38 publications

NeurIPS 2025 Dynamical Decoupling of Generalization and Overfitting in Large Two-Layer Networks Andrea Montanari, Pierfrancesco Urbani

FnTML 2024 A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists Andrea Montanari, Subhabrata Sen

NeurIPS 2024 Scaling Laws for Learning with Real and Surrogate Data Ayush Jain, Andrea Montanari, Eren Sasoglu

ICLR 2024 Towards a Statistical Theory of Data Selection Under Weak Supervision Germain Kolossov, Andrea Montanari, Pulkit Tandon

ICML 2023 Compressing Tabular Data via Latent Variable Estimation Andrea Montanari, Eric Weiner

COLT 2022 High-Dimensional Projection Pursuit: Outer Bounds and Applications to Interpolation in Neural Networks Kangjie Zhou, Andrea Montanari

JMLR 2022 Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander D'Amour, Katherine 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, Yian Ma, Cory 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

COLT 2022 Universality of Empirical Risk Minimization Andrea Montanari, Basil N. Saeed

COLT 2021 Learning with Invariances in Random Features and Kernel Models Song Mei, Theodor Misiakiewicz, Andrea Montanari

NeurIPS 2021 Streaming Belief Propagation for Community Detection Yuchen Wu, Jakab Tardos, Mohammadhossein Bateni, André Linhares, Filipe Miguel Goncalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard

COLT 2020 The Estimation Error of General First Order Methods Michael Celentano, Andrea Montanari, Yuchen Wu

NeurIPS 2020 When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari

ICML 2019 An Instability in Variational Inference for Topic Models Behrooz Ghorbani, Hamid Javadi, Andrea Montanari

NeurIPS 2019 Limitations of Lazy Training of Two-Layers Neural Network Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari

COLT 2019 Mean-Field Theory of Two-Layers Neural Networks: Dimension-Free Bounds and Kernel Limit Song Mei, Theodor Misiakiewicz, Andrea Montanari

AISTATS 2019 On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition Marco Mondelli, Andrea Montanari

NeurIPS 2018 Contextual Stochastic Block Models Yash Deshpande, Subhabrata Sen, Andrea Montanari, Elchanan Mossel

COLT 2018 Fundamental Limits of Weak Recovery with Applications to Phase Retrieval Marco Mondelli, Andrea Montanari

NeurIPS 2017 Inference in Graphical Models via Semidefinite Programming Hierarchies Murat A Erdogdu, Yash Deshpande, Andrea Montanari

COLT 2017 Solving SDPs for Synchronization and MaxCut Problems via the Grothendieck Inequality Song Mei, Theodor Misiakiewicz, Andrea Montanari, Roberto Imbuzeiro Oliveira

JMLR 2016 Sparse PCA via Covariance Thresholding Yash Deshpande, Andrea Montanari

NeurIPS 2015 Convergence Rates of Sub-Sampled Newton Methods Murat A Erdogdu, Andrea Montanari

COLT 2015 Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems Yash Deshpande, Andrea Montanari

NeurIPS 2015 On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors Andrea Montanari, Daniel Reichman, Ofer Zeitouni

NeurIPS 2014 A Statistical Model for Tensor PCA Emile Richard, Andrea Montanari

NeurIPS 2014 Cone-Constrained Principal Component Analysis Yash Deshpande, Andrea Montanari, Emile Richard

JMLR 2014 Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Adel Javanmard, Andrea Montanari

ICML 2014 Learning Mixtures of Linear Classifiers Yuekai Sun, Stratis Ioannidis, Andrea Montanari

NeurIPS 2014 Sparse PCA via Covariance Thresholding Yash Deshpande, Andrea Montanari

NeurIPS 2013 Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models Adel Javanmard, Andrea Montanari

NeurIPS 2013 Estimating LASSO Risk and Noise Level Mohsen Bayati, Murat A Erdogdu, Andrea Montanari

NeurIPS 2013 Model Selection for High-Dimensional Regression Under the Generalized Irrepresentability Condition Adel Javanmard, Andrea Montanari

UAI 2012 Guess Who Rated This Movie: Identifying Users Through Subspace Clustering Amy Zhang, Nadia Fawaz, Stratis Ioannidis, Andrea Montanari

NeurIPS 2010 Learning Networks of Stochastic Differential Equations José Pereira, Morteza Ibrahimi, Andrea Montanari

JMLR 2010 Matrix Completion from Noisy Entries Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh

NeurIPS 2010 The LASSO Risk: Asymptotic Results and Real World Examples Mohsen Bayati, José Pereira, Andrea Montanari

NeurIPS 2009 Matrix Completion from Noisy Entries Raghunandan Keshavan, Andrea Montanari, Sewoong Oh

NeurIPS 2009 Which Graphical Models Are Difficult to Learn? Andrea Montanari, Jose A. Pereira