3 papers
math.OC2026
Complexity of Projected Gradient Methods for Strongly Convex Optimization with Hölder Continuous Gradient Terms
Xiaojun Chen, C. T. Kelley, Lei Wang
This paper studies the complexity of projected gradient descent methods for a class of strongly convex constrained optimization problems where the objective function is expressed a…
math.OC2025
Bayesian distributionally robust variational inequalities: regularization and quantification
Wentao Ma, Zhiping Chen, Xiaojun Chen
We propose a Bayesian distributionally robust variational inequality (DRVI) framework that models the data-generating distribution through a finite mixture family, which allows us…
math.OC2025
A New Complexity Result for Strongly Convex Optimization with Locally -H{ö}lder Continuous Gradients
Xiaojun Chen, C. T. Kelley, Lei Wang
In this paper, we present a new complexity result for the gradient descent method with an appropriately fixed stepsize for minimizing a strongly convex function with locally -H{…