Author

Rujun Jiang

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Preprint Jul 2026

A Semismooth Newton Augmented Lagrangian Method for Sparse Spectral Risk Optimization

This work proposes a relative inexact proximal augmented Lagrangian method with a semismooth Newton subproblem solver for solving SRM-based optimization problems and provides explicit generalized Jacobian characterizations and tailor the pool adjacent violators algorithm for their efficient evaluation.

Rufeng Xiao, Rujun Jiang, Xudong Li et al. · 0 citations