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stat.ML2026
Isotropic Gaussian Processes Improve Vanilla Bayesian Optimization in High Dimensions
Wei-Ting Tang, Madhav Muthyala, Joel A. Paulson
High-dimensional Bayesian optimization (BO) often fits Gaussian process (GP) surrogates from far fewer observations than input dimensions. Modern Vanilla BO can perform well in thi…
cs.AI2026
Robust Regularized Policy Iteration under Transition Uncertainty
Hongqiang Lin, Zhenghui Fu, Weihao Tang +4
Offline reinforcement learning (RL) enables data-efficient and safe policy learning without online exploration, but its performance often degrades under distribution shift. The lea…