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math.OC2026
Achieving First-Order Statistical Improvements in Data-Driven Optimization: From No-Free-Lunch to Amplified Decision Perturbation
Henry Lam, Tianyu Wang
Recent proliferation of data-optimization integration has led to a range of methods that aim to improve the statistical performance of data-driven optimization decisions. However,…
math.OC2025
Revisit First-order Methods for Geodesically Convex Optimization
Yunlu Shu, Jiaxin Jiang, Lei Shi +1
In a seminal work of Zhang and Sra, gradient descent methods for geodesically convex optimization were comprehensively studied. In particular, Zhang and Sra derived a comparison in…
math.OC2025
Contextual Optimization under Covariate Shift: A Robust Approach by Intersecting Wasserstein Balls
Tianyu Wang, Ningyuan Chen, Chun Wang
In contextual optimization, a decision-maker leverages contextual information, often referred to as covariates, to better resolve uncertainty and make informed decisions. In this p…