Garvesh Raskutti
18 papers · 2008–2025 · 4 conferences · across top CS/AI conferences
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Conferences
JMLR (10)
NIPS (4)
AISTATS (2)
ICML (2)
Top co-authors
Keywords
graphical model
(3)
kernel methods
(3)
reproducing kernel hilbert space
(2)
randomized sketching
(2)
hyperparameter estimation
(2)
convex optimization
(2)
maximum likelihood estimation
(2)
statistical analysis
(2)
structure learning
(2)
least square
(2)
high-dimensional statistics
(2)
maximum likelihood
(2)
gaussian process
(2)
minimax optimization
(1)
graph structure
(1)
covariance estimation
(1)
sparse estimation
(1)
non-convex optimization
(1)
stochastic gradient descent
(1)
convergence analysis
(1)
Papers
Reliable and Scalable Variable Importance Estimation via Warm-start and Early Stopping
AISTATS 2025
Lazy Estimation of Variable Importance for Large Neural Networks
ICML 2022
Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits
JMLR 2022
A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration
JMLR 2021
Context-dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions
JMLR 2021
Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels
JMLR 2020
Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes
NIPS 2020
Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression
JMLR 2019
Estimating Network Structure from Incomplete Event Data
AISTATS 2019
Learning Quadratic Variance Function (QVF) DAG Models via OverDispersion Scoring (ODS)
JMLR 2018
A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares
JMLR 2016
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
NIPS 2015
Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares
ICML 2015
Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule
JMLR 2014
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
JMLR 2012
Restricted Eigenvalue Properties for Correlated Gaussian Designs
JMLR 2010
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness
NIPS 2009
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE
NIPS 2008