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stat.ML2024
Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Ashley Prater-Bennette +2
Distributionally robust optimization (DRO) is a powerful framework for training robust models against data distribution shifts. This paper focuses on constrained DRO, which has an…
math.OC2024
Sparse Recovery: The Square of Norms
Jianqing Jia, Ashley Prater-Bennette, Lixin Shen +1
This paper introduces a nonconvex approach for sparse signal recovery, proposing a novel model termed the -model, which utilizes the squared norms for this pur…
math.OC2024
Computing Proximity Operators of Scale and Signed Permutation Invariant Functions
Jianqing Jia, Ashley Prater-Bennette, Lixin Shen
This paper investigates the computation of proximity operators for scale and signed permutation invariant functions. A scale-invariant function remains unchanged under uniform scal…