High-dimensional Bayesian optimization with projections using quantile Gaussian processes
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DOI: 10.1007/s11590-019-01433-w
Abstract: Key challenges of Bayesian optimization in high dimensions are both learning the response surface and optimizing an acquisition function. The acquisition function selects a new point to evaluate the black-box function. Both challenges can be… read more here.
Keywords: dimensional bayesian; optimization; optimization projections; high dimensional ... See more keywords