Safe contextual Bayesian optimization tunes real-world PID controllers for room temperature, achieving 32% cost savings with explicit safety constraints.
Practical bayesian optimization of ma- chine learning algorithms
2 Pith papers cite this work. Polarity classification is still indexing.
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Proposes SIR-based supervised dimension reduction with kernel trick for high-dimensional Bayesian optimization, claims regret bounds and empirical gains on synthetic and real tasks.
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Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning
Safe contextual Bayesian optimization tunes real-world PID controllers for room temperature, achieving 32% cost savings with explicit safety constraints.
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High Dimensional Bayesian Optimization via Supervised Dimension Reduction
Proposes SIR-based supervised dimension reduction with kernel trick for high-dimensional Bayesian optimization, claims regret bounds and empirical gains on synthetic and real tasks.