Predictive entropy search for efficient global optimization of black-box functions
JM Hernández-Lobato, MW Hoffman… - Advances in neural …, 2014 - proceedings.neurips.cc
We propose a novel information-theoretic approach for Bayesian optimization called
Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that
maximizes the expected information gained with respect to the global maximum. PES
codifies this intractable acquisition function in terms of the expected reduction in the
differential entropy of the predictive distribution. This reformulation allows PES to obtain
approximations that are both more accurate and efficient than other alternatives such as …
Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that
maximizes the expected information gained with respect to the global maximum. PES
codifies this intractable acquisition function in terms of the expected reduction in the
differential entropy of the predictive distribution. This reformulation allows PES to obtain
approximations that are both more accurate and efficient than other alternatives such as …
Predictive entropy search for efficient global optimization of black-box functions
JM Henrández-Lobato, MW Hoffman… - Proceedings of the 27th …, 2014 - dl.acm.org
We propose a novel information-theoretic approach for Bayesian optimization called
Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that
maximizes the expected information gained with respect to the global maximum. PES
codifies this intractable acquisition function in terms of the expected reduction in the
differential entropy of the predictive distribution. This reformulation allows PES to obtain
approximations that are both more accurate and efficient than other alternatives such as …
Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that
maximizes the expected information gained with respect to the global maximum. PES
codifies this intractable acquisition function in terms of the expected reduction in the
differential entropy of the predictive distribution. This reformulation allows PES to obtain
approximations that are both more accurate and efficient than other alternatives such as …
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