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Greed Is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
11 references·1 citing·29 second hop
Greed Is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation (2021)Greed Is Good: Exploration and Exploitati…BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization (2019)BoTorch: A Framework for Effi…Max-value Entropy Search for Efficient Bayesian Optimization (2017)Max-value Entropy Search for …Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Taking the Human Out of the L…Practical Bayesian Optimization of Machine Learning Algorithms (2012)Practical Bayesian Optimizati…Convergence rates of efficient global optimization algorithms (2011)Convergence rates of efficien…Practical Bayesian optimization (2008)Practical Bayesian optimizati…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code (2000)A Comparison of Three Methods…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A Comparison of Three Methods…Computer experiments and global optimization (1997)Computer experiments and glob…Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Comparison of Three Methods f…A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise (1964)A New Method of Locating the …On the use of Wasserstein distance in the distributional analysis of human decision making under uncertainty (2022)On the use of Wasserstein dis…Design and Analysis of Computer Experiments (1989)A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning (2010)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Bayesian Optimization in a Billion Dimensions via Random Embeddings (2016)Constrained Bayesian Optimization with Noisy Experiments (2018)Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics (2021)Convergence properties of the expected improvement algorithm with fixed mean and covariance functions (2010)Non-probabilistic finite element analysis for parametric uncertainty treatment in applied mechanics: Recent advances (2010)A Nested Extreme Response Surface Approach for Time-Dependent Reliability-Based Design Optimization (2012)A review of techniques for parameter sensitivity analysis of environmental models (1994)Importance measures in global sensitivity analysis of nonlinear models (1996)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Scalable Bayesian Optimization Using Deep Neural Networks (2015)Bayesian Optimization (2018)Bayesian Optimization for Adaptive Experimental Design: A Review (2020)A Tutorial on Bayesian Optimization (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Portfolio allocation for Bayesian optimization (2011)Bayesian optimisation for Intelligent Environmental Monitoring (2012)Predictive Entropy Search for Efficient Global Optimization of Black-box Functions (2014)Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 (2021)Beyond playing 20 questions with nature: Integrative experiment design in the social and behavioral sciences (2022)HEBO: An Empirical Study of Assumptions in Bayesian Optimisation (2022)A distribution-free approach to inducing rank correlation among input variables (1982)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Uniform Design: Theory and Application (2000)Hybrid simulation–optimization methods: A taxonomy and discussion (2014)Time-dependent reliability of aging structures in the presence of non-stationary loads and degradation (2014)Design of computer experiments: A review (2017)
this work references cited by second hop

References

  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code8,233 cited
  • 2012Practical Bayesian Optimization of Machine Learning Algorithms6,690 cited
  • 2015Taking the Human Out of the Loop: A Review of Bayesian Optimization6,126 cited
  • 1979Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code3,238 cited
  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code2,856 cited
  • 1964A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise1,084 cited
  • 2019BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization515 cited
  • 2011Convergence rates of efficient global optimization algorithms454 cited
  • 1997Computer experiments and global optimization375 cited
  • 2008Practical Bayesian optimization222 cited
  • 2017Max-value Entropy Search for Efficient Bayesian Optimization211 cited

Cited by

  • 2022On the use of Wasserstein distance in the distributional analysis of human decision making under uncertainty8 cited

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