The Parallel Knowledge Gradient Method for Batch Bayesian Optimization
暂无分享,去创建一个
[1] Dong Yu,et al. Deep Learning: Methods and Applications , 2014, Found. Trends Signal Process..
[2] Matt J. Kusner,et al. Bayesian Optimization with Inequality Constraints , 2014, ICML.
[3] Nicolas Vayatis,et al. Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration , 2013, ECML/PKDD.
[4] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[5] S. P. Smith. Differentiation of the Cholesky Algorithm , 1995 .
[6] Warren B. Powell,et al. The Knowledge-Gradient Policy for Correlated Normal Beliefs , 2009, INFORMS J. Comput..
[7] Jasper Snoek,et al. Bayesian Optimization with Unknown Constraints , 2014, UAI.
[8] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[9] D. Ginsbourger,et al. Kriging is well-suited to parallelize optimization , 2010 .
[10] Dick Wick Hall,et al. Elementary Real Analysis , 1971 .
[11] Jasper Snoek,et al. Input Warping for Bayesian Optimization of Non-Stationary Functions , 2014, ICML.
[12] Jasper Snoek,et al. Multi-Task Bayesian Optimization , 2013, NIPS.
[13] Warren B. Powell,et al. Nested-Batch-Mode Learning and Stochastic Optimization with An Application to Sequential MultiStage Testing in Materials Science , 2015, SIAM J. Sci. Comput..
[14] P. L’Ecuyer,et al. A Unified View of the IPA, SF, and LR Gradient Estimation Techniques , 1990 .
[15] Andreas Krause,et al. Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization , 2012, ICML.
[16] Matthew W. Hoffman,et al. Predictive Entropy Search for Efficient Global Optimization of Black-box Functions , 2014, NIPS.
[17] Zoubin Ghahramani,et al. Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions , 2015, NIPS.
[18] R JonesDonald,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998 .
[19] Warren B. Powell,et al. The Correlated Knowledge Gradient for Simulation Optimization of Continuous Parameters using Gaussian Process Regression , 2011, SIAM J. Optim..
[20] David Ginsbourger,et al. Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection , 2013, LION.
[21] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[22] Andreas Krause,et al. Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting , 2009, IEEE Transactions on Information Theory.
[23] David Ginsbourger,et al. Differentiating the Multipoint Expected Improvement for Optimal Batch Design , 2015, MOD.