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math.OC2026
A Semismooth Newton Augmented Lagrangian Method for Sparse Spectral Risk Optimization
Rufeng Xiao, Rujun Jiang, Xudong Li +1
Empirical risk minimization is a standard and effective paradigm for learning predictive models by minimizing average loss. In high-stakes decision-making, however, an average-loss…
math.OC2026
Solving Chance Constrained Programs via a Penalty based Difference of Convex Approach
Zhiping Li, Nan Jiang, Rujun Jiang
We develop two penalty based difference of convex (DC) algorithms for solving chance constrained programs. First, leveraging a rank-based DC decomposition of the chance constraint,…