← Authors

Andrea Montanari

35 papers · 2009–2024 · 6 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (15) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (5) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (16) πŸ† Keyword Champion πŸ‘₯ Mega-Team (40) πŸ’Ž Century Club (35) ⚑ Prolific Year (5) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (62) ❓ The Questioner (2) πŸ”₯ Unstoppable (12)

Conferences

NIPS (18) COLT (8) JMLR (4) ICML (3) AISTATS (1) ICLR (1)

Top co-authors

Yash Deshpande (6) Theodor Misiakiewicz (5) Song Mei (5) Behrooz Ghorbani (3) Murat A Erdogdu (3) Adel Javanmard (3) JosΓ© Pereira (2) Yuchen Wu (2) Mohsen Bayati (2) Marco Mondelli (2)

Research topics

Statistics (3)

Keywords

hypothesis testing (4) neural network (4) spectral method (4) high-dimensional regression (3) high-dimensional statistics (3) lasso regression (3) neural tangent kernel (3) information theory (3) principal component analysis (3) graphical model (3) network inference (2) sparse principal component analysis (2) statistical learning (2) matrix completion (2) model selection (2) stochastic gradient descent (2) tensor decomposition (2) community detection (2) graph clustering (2) semidefinite programming (2)

Papers

Scaling laws for learning with real and surrogate data NIPS 2024
Towards a statistical theory of data selection under weak supervision ICLR 2024
Compressing Tabular Data via Latent Variable Estimation ICML 2023
Underspecification Presents Challenges for Credibility in Modern Machine Learning JMLR 2022
Universality of empirical risk minimization COLT 2022
High-Dimensional Projection Pursuit: Outer Bounds and Applications to Interpolation in Neural Networks COLT 2022
Learning with invariances in random features and kernel models COLT 2021
Streaming Belief Propagation for Community Detection NIPS 2021
When Do Neural Networks Outperform Kernel Methods? NIPS 2020
The estimation error of general first order methods COLT 2020
An Instability in Variational Inference for Topic Models ICML 2019
Limitations of Lazy Training of Two-layers Neural Network NIPS 2019
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition AISTATS 2019
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit COLT 2019
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval COLT 2018
Contextual Stochastic Block Models NIPS 2018
Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality COLT 2017
Inference in Graphical Models via Semidefinite Programming Hierarchies NIPS 2017
Sparse PCA via Covariance Thresholding JMLR 2016
Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems COLT 2015
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors NIPS 2015
Convergence rates of sub-sampled Newton methods NIPS 2015
Sparse PCA via Covariance Thresholding NIPS 2014
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression JMLR 2014
Cone-Constrained Principal Component Analysis NIPS 2014
A statistical model for tensor PCA NIPS 2014
Learning Mixtures of Linear Classifiers ICML 2014
Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition NIPS 2013
Estimating LASSO Risk and Noise Level NIPS 2013
Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models NIPS 2013
Matrix Completion from Noisy Entries JMLR 2010
The LASSO risk: asymptotic results and real world examples NIPS 2010
Learning Networks of Stochastic Differential Equations NIPS 2010
Matrix Completion from Noisy Entries NIPS 2009
Which graphical models are difficult to learn? NIPS 2009