Approximating Pareto Frontiers in Stochastic Multi-Objective Optimization via Hashing and Randomization

arXiv:2604.01098v1 Announce Type: cross Abstract: Stochastic Multi-Objective Optimization (SMOO) is critical for decision-making trading off multiple potentially conflicting objectives in uncertain environments. SMOO aims at identifying the Pareto frontier, which contains all mutually non-dominating decisions. The problem is highly intractable due to the embedded probabilistic inference, such as computing the marginal, posterior probabilities, or expectations. Existing methods, such as scalariza