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Differentiating the Multipoint Expected Improvement for Optimal Batch Design
12 references·0 citing·38 second hop
Differentiating the Multipoint Expected Improvement for Optimal Batch Design (2015)Differentiating the Multipoint Expected I…Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection (2013)Fast Computation of the Multi…Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization (2012)Parallelizing Exploration-Exp…Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Information-Theoretic Regret …DiceKriging , DiceOptim : Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization (2012)DiceKriging , DiceOptim : Two…Convergence rates of efficient global optimization algorithms (2011)Convergence rates of efficien…Towards Gaussian Process-based Optimization with Finite Time Horizon (2010)Towards Gaussian Process-base…Convergence properties of the expected improvement algorithm with fixed mean and covariance functions (2010)Convergence properties of the…A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning (2010)A Tutorial on Bayesian Optimi…A Knowledge-Gradient Policy for Sequential Information Collection (2008)A Knowledge-Gradient Policy f…Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Algorithmic construction of optimal symmetric Latin hypercube designs (2000)Algorithmic construction of o…Computer experiments and global optimization (1997)Computer experiments and glob…Design and Analysis of Computer Experiments (1989)STATISTICS FOR SPATIAL DATA (1992)Global Sensitivity Analysis. The Primer (2007)BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits (2014)Simulation optimization: a review of algorithms and applications (2015)Adaptive approaches in metamodel-based reliability analysis: A review (2020)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Minimax and maximin distance designs (1990)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)ORTHOGONAL-MAXIMIN LATIN HYPERCUBE DESIGNS (2008)An algorithm for fast optimal Latin hypercube design of experiments (2009)Design of computer experiments: A review (2017)Design and Analysis of Experiments for Statistical Selection, Screening and Multiple Comparisons (1996)Simulation Budget Allocation for Further Enhancing the Efficiency of Ordinal Optimization (2000)The Knowledge-Gradient Policy for Correlated Normal Beliefs (2009)A Tutorial on Thompson Sampling (2018)A unified framework for stochastic optimization (2018)Geostatistics: Modeling Spatial Uncertainty (2000)Interpolation of Spatial Data: Some Theory for Kriging (2000)Hierarchical Knowledge Gradient for Sequential Sampling (2011)Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations (2012)Parallel Bayesian Global Optimization of Expensive Functions (2020)Advances in prospect theory: Cumulative representation of uncertainty (1992)The Adaptive Decision Maker (1994)A Tutorial on Bayesian Optimization (2018)Bayesian Optimization (2018)Some aspects of the sequential design of experiments (1952)Parallel Gaussian process optimization with upper confidence bound and pure exploration (2013)Batched Large-scale Bayesian Optimization in High-dimensional Spaces (2017)Parallelised Bayesian Optimisation via Thompson Sampling (2018)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)Prediction, Learning, and Games (2006)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Bandit Algorithms (2020)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)
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References

  • 2002Finite-time Analysis of the Multiarmed Bandit Problem5,980 cited
  • 2012Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting2,098 cited
  • 2010A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning2,053 cited
  • 2012DiceKriging , DiceOptim : Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization594 cited
  • 2011Convergence rates of efficient global optimization algorithms454 cited
  • 2008A Knowledge-Gradient Policy for Sequential Information Collection447 cited
  • 2000Algorithmic construction of optimal symmetric Latin hypercube designs429 cited
  • 1997Computer experiments and global optimization375 cited
  • 2012Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization340 cited
  • 2010Convergence properties of the expected improvement algorithm with fixed mean and covariance functions183 cited
  • 2013Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection145 cited
  • 2010Towards Gaussian Process-based Optimization with Finite Time Horizon44 cited

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