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From Dual Tracking to Clipping: Provably Faster Distributionally Robust Multi-Objective Optimization
Multi-objective optimization (MOO) has received growing attention in applications that require learning under multiple criteria. However, most existing MOO formulations do not explicitly account for distributional shifts in the data. We introduce distributionally robust multi-objective optimization
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