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Found 3 papers, 2 papers with code
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Sequential optimization methods are often confronted with the curse of dimensionality in high-dimensional spaces.
An Invariant Information Geometric Method for High-Dimensional Online Optimization
In this paper, we introduce a full invariance oriented evolution strategies algorithm, derived from its corresponding framework, that effectively rivals the leading Bayesian optimization method in tasks with dimensions at the upper limit of Bayesian capability.
Safe Policy Optimization with Local Generalized Linear Function Approximations
Safe exploration is a key to applying reinforcement learning (RL) in safety-critical systems.
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