3 papers
math.OC2026
Lipschitz Regularity in Wasserstein Robust Stochastic Optimal Control
Shengbo Wang, Jose Blanchet
Robust Markov decision processes provide a principled framework for protecting sequential decision-making against transition-law misspecification and have attracted substantial rec…
math.OC2026
Fast Convergence of Policy Regret in Learning Stochastic Optimal Control
Shengbo Wang, Jose Blanchet, Peter Glynn
Policy learning in modern operations environments faces a fundamental tension between limited operational data and the large, often continuous, state and action spaces over which g…
cs.AI2026
FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains
Jiashuo Liu, Siyuan Chen, Zaiyuan Wang +38
Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, Futu…