On the Convergence Rates of Expected Improvement Methods
暂无分享,去创建一个
[1] Adam D. Bull,et al. Convergence Rates of Efficient Global Optimization Algorithms , 2011, J. Mach. Learn. Res..
[2] Benjamin Van Roy,et al. Learning to Optimize via Posterior Sampling , 2013, Math. Oper. Res..
[3] Chun-Hung Chen,et al. Opportunity Cost and OCBA Selection Procedures in Ordinal Optimization for a Fixed Number of Alternative Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[4] Éva Tardos,et al. Algorithm design , 2005 .
[5] Warren B. Powell,et al. Finite-time Analysis for the Knowledge-Gradient Policy , 2016, SIAM J. Control. Optim..
[6] Stephen E. Chick,et al. New Two-Stage and Sequential Procedures for Selecting the Best Simulated System , 2001, Oper. Res..
[7] Barry L. Nelson,et al. A brief introduction to optimization via simulation , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).
[8] Jürgen Branke,et al. Selecting a Selection Procedure , 2007, Manag. Sci..
[9] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[10] Warren B. Powell,et al. The Knowledge-Gradient Policy for Correlated Normal Beliefs , 2009, INFORMS J. Comput..
[11] Thorsten Dickhaus,et al. Asymptotic Tail Properties of Student's t-Distribution , 2008 .
[12] Andrew P. Soms. Rational Bounds for the t-Tail Area , 1980 .
[13] Stephen E. Chick,et al. Economic Analysis of Simulation Selection Problems , 2009, Manag. Sci..
[14] Peter W. Glynn,et al. Ordinal optimization: A nonparametric framework , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).
[15] Ilya O. Ryzhov. Expected improvement is equivalent to OCBA , 2015, 2015 Winter Simulation Conference (WSC).
[16] Stephen E. Chick,et al. Chapter 9 Subjective Probability and Bayesian Methodology , 2006, Simulation.
[17] S. Gupta,et al. Bayesian look ahead one-stage sampling allocations for selection of the best population , 1996 .
[18] Warren B. Powell,et al. A Knowledge-Gradient Policy for Sequential Information Collection , 2008, SIAM J. Control. Optim..
[19] Warren B. Powell,et al. Information Collection on a Graph , 2011, Oper. Res..
[20] Loo Hay Lee,et al. Stochastically Constrained Ranking and Selection via SCORE , 2014, ACM Trans. Model. Comput. Simul..
[21] Leyuan Shi,et al. An optimal opportunity cost selection procedure for a fixed number of designs , 2014, Proceedings of the Winter Simulation Conference 2014.
[22] Huashuai Qu,et al. Simulation optimization: A tutorial overview and recent developments in gradient-based methods , 2014, Proceedings of the Winter Simulation Conference 2014.
[23] Barry L. Nelson,et al. Recent advances in ranking and selection , 2007, 2007 Winter Simulation Conference.
[24] Boris Defourny,et al. Efficient learning of donor retention strategies for the American Red Cross , 2013, 2013 Winter Simulations Conference (WSC).
[25] Loo Hay Lee,et al. Stochastic Simulation Optimization - An Optimal Computing Budget Allocation , 2010, System Engineering and Operations Research.
[26] Ilya O. Ryzhov,et al. Optimal learning with non-Gaussian rewards , 2013, 2013 Winter Simulations Conference (WSC).
[27] Loo Hay Lee,et al. Ranking and Selection: Efficient Simulation Budget Allocation , 2015 .
[28] T. L. Lai Andherbertrobbins. Asymptotically Efficient Adaptive Allocation Rules , 1985 .
[29] Andrew P. Soms,et al. An Asymptotic Expansion for the Tail Area of the t -Distribution , 1976 .
[30] Loo Hay Lee,et al. Efficient Simulation Budget Allocation for Selecting an Optimal Subset , 2008, INFORMS J. Comput..
[31] Warren B. Powell,et al. The Knowledge Gradient Algorithm for a General Class of Online Learning Problems , 2012, Oper. Res..
[32] Huashuai Qu,et al. Sequential Selection with Unknown Correlation Structures , 2015, Oper. Res..
[33] M. Degroot. Optimal Statistical Decisions , 1970 .
[34] Peter W. Glynn,et al. A large deviations perspective on ordinal optimization , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..
[35] Chun-Hung Chen,et al. Simulation Allocation for Determining the Best Design in the Presence of Correlated Sampling , 2007, INFORMS J. Comput..
[36] Warren B. Powell,et al. Paradoxes in Learning and the Marginal Value of Information , 2010, Decis. Anal..
[37] Avraham Adler,et al. Lambert-W Function , 2015 .
[38] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[39] Loo Hay Lee,et al. Efficient simulation budget allocation with regression , 2013 .
[40] Chun-Hung Chen,et al. Simulation Budget Allocation for Further Enhancing the Efficiency of Ordinal Optimization , 2000, Discret. Event Dyn. Syst..
[41] Jürgen Branke,et al. Sequential Sampling to Myopically Maximize the Expected Value of Information , 2010, INFORMS J. Comput..
[42] Warren B. Powell,et al. Optimal Learning: Powell/Optimal , 2012 .
[43] S. Jain,et al. CALIBRATING SIMULATION MODELS USING THE KNOWLEDGE GRADIENT WITH CONTINUOUS PARAMETERS , 2010 .