← Authors

Raghu Meka

25 papers · 2009–2024 · 5 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (15) πŸ—ΊοΈ Taxonomy Completionist (12) 🐝 Cross-Pollinator (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (6) πŸ† Keyword Champion πŸ”¬ Deep Specialist (11) 🌱 Topic Pioneer πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter πŸ’Ž Century Club (25) ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (121)

Conferences

COLT (12) NIPS (9) ICML (2) EMNLP (1) ICLR (1)

Top co-authors

Adam Klivans (7) Sitan Chen (5) Pritish Kamath (4) Jonathan Kelner (4) Frederic Koehler (4) Chiyuan Zhang (3) Nishanth Dikkala (3) Pasin Manurangsi (3) Badih Ghazi (3) Ravi Kumar (3)

Research topics

Differential Privacy (1)

Keywords

sparse linear regression (4) pac learning (4) neural network (4) relu network (3) convex optimization (3) low-rank matrix (3) matrix completion (3) agnostic learning (2) learning theory (2) gaussian graphical model (2) low-rank recovery (2) differential privacy (2) halfspace learning (2) query complexity (2) high-dimensional statistics (1) theoretical analysis (1) compressed sensing (1) computational complexity (1) image classification (1) dimensionality reduction (1)

Papers

On Convex Optimization with Semi-Sensitive Features COLT 2024
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps COLT 2024
Learning Neural Networks with Sparse Activations COLT 2024
Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension COLT 2024
Learning Narrow One-Hidden-Layer ReLU Networks COLT 2023
User-Level Differential Privacy With Few Examples Per User NIPS 2023
On User-Level Private Convex Optimization ICML 2023
On the Benefits of Learning to Route in Mixture-of-Experts Models EMNLP 2023
Feature Adaptation for Sparse Linear Regression NIPS 2023
Sketching based Representations for Robust Image Classification with Provable Guarantees NIPS 2022
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks NIPS 2022
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs NIPS 2022
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs ICLR 2022
Efficiently Learning One Hidden Layer ReLU Networks From Queries NIPS 2021
Learning Polynomials in Few Relevant Dimensions COLT 2020
Balancing Gaussian vectors in high dimension COLT 2020
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds NIPS 2020
Efficient Algorithms for Outlier-Robust Regression COLT 2018
Learning One Convolutional Layer with Overlapping Patches ICML 2018
Computational Limits for Matrix Completion COLT 2014
Volumetric Spanners: an Efficient Exploration Basis for Learning COLT 2014
Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching COLT 2013
Learning Functions of Halfspaces Using Prefix Covers COLT 2012
Guaranteed Rank Minimization via Singular Value Projection NIPS 2010
Matrix Completion from Power-Law Distributed Samples NIPS 2009