3 papers
stat.ML2026
Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models
Yilin Zheng, Haowei Wang, Szu Hui Ng +1
Bayesian optimization (BO) is a widely used approach for black-box optimization that uses a Gaussian process (GP) as a surrogate and guides sequential evaluations via an acquisitio…
cs.LG2026
Curiosity is Knowledge: Self-Consistent Learning and No-Regret Optimization with Active Inference
Yingke Li, Anjali Parashar, Enlu Zhou +1
Active inference (AIF) unifies exploration and exploitation by minimizing the Expected Free Energy (EFE), balancing epistemic value (information gain) and pragmatic value (task per…
math.OC2025
Bayesian Risk-averse Model Predictive Control with Consistency and Stability Guarantees
Yingke Li, Yifan Lin, Enlu Zhou +1
Model Predictive Control (MPC) is a powerful framework for constrained control, but its performance and safety can be severely degraded when the prediction model is learned online…