2 citations · 4 across the 17 of their papers we have counts for
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Distributional Robustness Bounds Generalization Errors
Shixiong Wang, Haowei Wang
Bayesian methods, distributionally robust optimization methods, and regularization methods are three pillars of trustworthy machine learning combating distributional uncertainty, e…
A model aggregation approach for high-dimensional large-scale optimization
Haowei Wang, Ercong Zhang, Szu Hui Ng +1
Bayesian optimization (BO) has been widely used in machine learning and simulation optimization. With the increase in computational resources and storage capacities in these fields…
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
Shouri Hu, Haowei Wang, Zhongxiang Dai +2
The expected improvement (EI) is one of the most popular acquisition functions for Bayesian optimization (BO) and has demonstrated good empirical performances in many applications…
Enhanced Global Optimization with Parallel Global and Local Structures
Haowei Wang, Songhao Wang, Qun Meng +1
In practice, objective functions of real-time control systems can have multiple local minimums or can dramatically change over the function space, making them hard to optimize. To…