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math.OC2026
Uncertainty Quantification in Data-Driven Inverse Optimization via Bayesian Inference
Timothy C. Y. Chan, Nathan Sandholtz, Nasrin Yousefi
Inverse optimization (IO) is used to estimate unknown parameters of an optimization model from observed decisions. In the data-driven context, the estimated parameters are inherent…
math.OC2024
Exact sensitivity analysis of Markov reward processes via algebraic geometry
Timothy C. Y. Chan, Muhammad Maaz
We introduce a new approach for deterministic sensitivity analysis of Markov reward processes, commonly used in cost-effectiveness analyses, via reformulation into a polynomial sys…