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Resources

Global optimization of Lipschitz functions.

  • C. Malherbe and N. Vayatis. "Global optimization of Lipschitz functions". ICML. 2314 - 2323. (2017)

BayesOpt

  • R. Martinez-Cantin. BayesOpt: {A} Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits. CoRR. 1405.7430. (2014)

CMA-ES - Covariance Matrix Adaptation Evolution Strategy

  • N. Hansen. The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañaga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. Springer, pp. 75-102 (2006).

IS ABOVE POINTING AT THE CORRECT PAPER?

CRS - Controlled Random Search with Local Mutation

  • P. Kaelo and M. M. Ali, "Some variants of the controlled random search algorithm for global optimization," J. Optim. Theory Appl. 130 (2), 253-264 (2006).

DIRECT

  • D. R. Jones, C. D. Perttunen, and B. E. Stuckmann, "Lipschitzian optimization without the lipschitz constant," J. Optimization Theory and Applications, vol. 79, p. 157 (1993).

MLSL - Multi-Level Single-Linkage

  • A. H. G. Rinnooy Kan and G. T. Timmer, "Stochastic global optimization methods," Mathematical Programming, vol. 39, p. 27-78 (1987). (Actually 2 papers — part I: clustering methods, p. 27, then part II: multilevel methods, p. 57.)