Raskutti, Garvesh

17 publications

AISTATS 2025 Reliable and Scalable Variable Importance Estimation via Warm-Start and Early Stopping Zexuan Sun, Garvesh Raskutti

JMLR 2022 Gaussian Process Parameter Estimation Using Mini-Batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits Hao Chen, Lili Zheng, Raed Al Kontar, Garvesh Raskutti

ICML 2022 Lazy Estimation of Variable Importance for Large Neural Networks Yue Gao, Abby Stevens, Garvesh Raskutti, Rebecca Willett

JMLR 2021 A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration Yuetian Luo, Garvesh Raskutti, Ming Yuan, Anru R. Zhang

JMLR 2021 Context-Dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions Lili Zheng, Garvesh Raskutti, Rebecca Willett, Benjamin Mark

JMLR 2020 Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels Hyebin Song, Ran Dai, Garvesh Raskutti, Rina Foygel Barber

NeurIPS 2020 Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes Hao Chen, Lili Zheng, Raed AL Kontar, Garvesh Raskutti

AISTATS 2019 Estimating Network Structure from Incomplete Event Data Benjamin Mark, Garvesh Raskutti, Rebecca Willett

JMLR 2019 Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression Han Chen, Garvesh Raskutti, Ming Yuan

JMLR 2016 A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares Garvesh Raskutti, Michael W. Mahoney

NeurIPS 2015 Learning Large-Scale Poisson DAG Models Based on OverDispersion Scoring Gunwoong Park, Garvesh Raskutti

ICML 2015 Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares Garvesh Raskutti, Michael Mahoney

JMLR 2014 Early Stopping and Non-Parametric Regression: An Optimal Data-Dependent Stopping Rule Garvesh Raskutti, Martin J. Wainwright, Bin Yu

JMLR 2012 Minimax-Optimal Rates for Sparse Additive Models over Kernel Classes via Convex Programming Garvesh Raskutti, Martin J. Wainwright, Bin Yu

JMLR 2010 Restricted Eigenvalue Properties for Correlated Gaussian Designs Garvesh Raskutti, Martin J. Wainwright, Bin Yu

NeurIPS 2009 Lower Bounds on Minimax Rates for Nonparametric Regression with Additive Sparsity and Smoothness Garvesh Raskutti, Bin Yu, Martin J. Wainwright

NeurIPS 2008 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-Regularized MLE Garvesh Raskutti, Bin Yu, Martin J. Wainwright, Pradeep K. Ravikumar