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Stochastic Optimization and Sparse Statistical Recovery: An Optimal Algorithm for High Dimensions
High Dimensional Robust Sparse Regression
2021 Stochastics and Statistics Seminar - Jerry Li
Approximation Algorithms for Stochastic Optimization II
Learning Sparse Data with Near-optimal Speed and Efficiency from a Variety of Measurement Processes
Stephen Wright: "Sparse and Regularized Optimization, Pt. 2"
Two basic problems in finite stochastic optimization
Machine Learning Work Shop- A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem
The estimation error of general first order methods
Sparse and Smooth: Convex relaxation for high-dim kernel regression
The Theoretical Limits of Statistical High Dimensional Nearest Neighbor Algor...
Computational Trade-Offs in Statistical Learning: An Optimization Perspective
