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Constrained Optimization of Rank-One Functions with Indicator Variables
We then demonstrate that extended representations of sets associated with epigraphs of rank-one convex functions over constraints modeling indicator relations naturally admit such a conic representation.
Wasserstein Distributionally Robust Estimation in High Dimensions: Performance Analysis and Optimal Hyperparameter Tuning
Wasserstein distributionally robust optimization has recently emerged as a powerful framework for robust estimation, enjoying good out-of-sample performance guarantees, well-understood regularization effects, and computationally tractable reformulations.
Mean-Covariance Robust Risk Measurement
We introduce a universal framework for mean-covariance robust risk measurement and portfolio optimization.
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