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Found 12 papers, 3 papers with code
Achieving Diversity in Objective Space for Sample-efficient Search of Multiobjective Optimization Problems
Efficiently solving multi-objective optimization problems for simulation optimization of important scientific and engineering applications such as materials design is becoming an increasingly important research topic.
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
It was based on tuning (validation set) performance of standard machine learning models on real datasets.
Efficient Rollout Strategies for Bayesian Optimization
Non-myopic acquisition functions consider the impact of the next $h$ function evaluations and are typically computed through rollout, in which $h$ steps of BO are simulated.
Sampling Humans for Optimizing Preferences in Coloring Artwork
Many circumstances of practical importance have performance or success metrics which exist implicitly---in the eye of the beholder, so to speak.
Bayesian Optimization with Approximate Set Kernels
We propose a practical Bayesian optimization method over sets, to minimize a black-box function that takes a set as a single input.
Sequential Preference-Based Optimization
Many real-world engineering problems rely on human preferences to guide their design and optimization.
Practical Bayesian optimization in the presence of outliers
In this paper, we present an empirical evaluation of Bayesian optimization methods in the presence of outliers.
Robust Bayesian Optimization with Student-t Likelihood
Bayesian optimization has recently attracted the attention of the automatic machine learning community for its excellent results in hyperparameter tuning.
Bayesian Optimization for Machine Learning : A Practical Guidebook
The engineering of machine learning systems is still a nascent field; relying on a seemingly daunting collection of quickly evolving tools and best practices.
Interactive Preference Learning of Utility Functions for Multi-Objective Optimization
Real-world engineering systems are typically compared and contrasted using multiple metrics.
Optimization and Control 90C29, 90B50
Evaluation System for a Bayesian Optimization Service
Bayesian optimization is an elegant solution to the hyperparameter optimization problem in machine learning.
A Stratified Analysis of Bayesian Optimization Methods
Empirical analysis serves as an important complement to theoretical analysis for studying practical Bayesian optimization.
