Acquisition Function-Guided Generation for Bayesian Optimization over Discrete Spaces
Bayesian optimization (BO) over discrete spaces is challenging due to missing gradients and the sparsity of valid solutions. Latent-space BO sidesteps both issues by fitting a surrogate in the latent space of a generative model, which however substantially complicates the direct incorporation of domain knowledge that i...
Tommaso Ancilli, Thomas Wedenig, Henry Moss et al.
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