Meka, Raghu

26 publications

NeurIPS 2025 Smoothed Agnostic Learning of Halfspaces over the Hypercube Yiwen Kou, Raghu Meka

COLT 2024 Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps Jonathan Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi

COLT 2024 Learning Neural Networks with Sparse Activations Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka

COLT 2024 On Convex Optimization with Semi-Sensitive Features Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

COLT 2024 Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension Gautam Chandrasekaran, Adam Klivans, Vasilis Kontonis, Raghu Meka, Konstantinos Stavropoulos

NeurIPS 2023 Feature Adaptation for Sparse Linear Regression Jonathan Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi

COLT 2023 Learning Narrow One-Hidden-Layer ReLU Networks Sitan Chen, Zehao Dou, Surbhi Goel, Adam Klivans, Raghu Meka

ICML 2023 On User-Level Private Convex Optimization Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPS 2023 User-Level Differential Privacy with Few Examples per User Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPS 2022 Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks Sitan Chen, Aravind Gollakota, Adam Klivans, Raghu Meka

NeurIPS 2022 Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs Jonathan Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi

ICLR 2022 Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka

NeurIPS 2022 Sketching Based Representations for Robust Image Classification with Provable Guarantees Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang

NeurIPS 2021 Efficiently Learning One Hidden Layer ReLU Networks from Queries Sitan Chen, Adam Klivans, Raghu Meka

COLT 2020 Balancing Gaussian Vectors in High Dimension Paxton Turner, Raghu Meka, Philippe Rigollet

COLT 2020 Learning Polynomials in Few Relevant Dimensions Sitan Chen, Raghu Meka

NeurIPS 2020 Learning Some Popular Gaussian Graphical Models Without Condition Number Bounds Jonathan Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra

COLT 2018 Efficient Algorithms for Outlier-Robust Regression Adam R. Klivans, Pravesh K. Kothari, Raghu Meka

ICML 2018 Learning One Convolutional Layer with Overlapping Patches Surbhi Goel, Adam Klivans, Raghu Meka

COLT 2014 Computational Limits for Matrix Completion Moritz Hardt, Raghu Meka, Prasad Raghavendra, Benjamin Weitz

COLT 2014 Volumetric Spanners: An Efficient Exploration Basis for Learning Elad Hazan, Zohar Shay Karnin, Raghu Meka

COLT 2013 Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching Daniel M. Kane, Adam R. Klivans, Raghu Meka

COLT 2012 Learning Functions of Halfspaces Using Prefix Covers Parikshit Gopalan, Adam R. Klivans, Raghu Meka

NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection Prateek Jain, Raghu Meka, Inderjit S. Dhillon

NeurIPS 2009 Matrix Completion from Power-Law Distributed Samples Raghu Meka, Prateek Jain, Inderjit S. Dhillon

ICML 2008 Rank Minimization via Online Learning Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon