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stat.ME2025
Exact Coordinate Descent for High-Dimensional Regularized Huber Regression
Younghoon Kim, Po-Ling Loh, Sumanta Basu
This study develops a coordinate descent algorithm for high-dimensional Huber regression with an elastic-net penalty. Unlike existing gradient descent algorithms and coordinate des…
math.ST2025
On the Benefits of Accelerated Optimization in Robust and Private Estimation
Laurentiu Andrei Marchis, Po-Ling Loh
We study the advantages of accelerated gradient methods, specifically based on the Frank-Wolfe method and projected gradient descent, for privacy and heavy-tailed robustness. Our a…