Multiplicative Up-Drift
暂无分享,去创建一个
[1] Weijie Zheng,et al. Sharp Bounds for Genetic Drift in Estimation of Distribution Algorithms , 2020, IEEE Transactions on Evolutionary Computation.
[2] Benjamin Doerr,et al. Probabilistic Tools for the Analysis of Randomized Optimization Heuristics , 2018, Theory of Evolutionary Computation.
[3] Johannes Lengler,et al. Drift Analysis , 2017, Theory of Evolutionary Computation.
[4] Thomas Bäck,et al. Theory of Evolutionary Computation: Recent Developments in Discrete Optimization , 2020, Theory of Evolutionary Computation.
[5] Benjamin Doerr,et al. Sharp Bounds for Genetic Drift in EDAs , 2019, ArXiv.
[6] Benjamin Doerr,et al. The efficiency threshold for the offspring population size of the (µ, λ) EA , 2019, GECCO.
[7] Benjamin Doerr,et al. Analyzing randomized search heuristics via stochastic domination , 2019, Theor. Comput. Sci..
[8] P. Lehre,et al. Level-Based Analysis of the Univariate Marginal Distribution Algorithm , 2018, Algorithmica.
[9] Benjamin Doerr,et al. A tight runtime analysis for the (μ + λ) EA , 2018, GECCO.
[10] Per Kristian Lehre,et al. University of Birmingham Level-based analysis of the population-based incremental learning algorithm , 2018 .
[11] Martin S. Krejca,et al. Intuitive Analyses via Drift Theory , 2018 .
[12] Martin S. Krejca,et al. First-Hitting Times Under Additive Drift , 2018, PPSN.
[13] Benjamin Doerr,et al. Better Runtime Guarantees via Stochastic Domination , 2018, EvoCOP.
[14] Benjamin Doerr,et al. An Elementary Analysis of the Probability That a Binomial Random Variable Exceeds Its Expectation , 2017, Statistics & Probability Letters.
[15] OneMax,et al. EA on Generalized Dynamic OneMax , 2018 .
[16] Benjamin Doerr,et al. Optimal Static and Self-Adjusting Parameter Choices for the $$(1+(\lambda ,\lambda ))$$(1+(λ,λ)) Genetic Algorithm , 2017, Algorithmica.
[17] Per Kristian Lehre,et al. Improved runtime bounds for the univariate marginal distribution algorithm via anti-concentration , 2017, GECCO.
[18] Duc-Cuong Dang,et al. Level-Based Analysis of Genetic Algorithms and Other Search Processes , 2014, bioRxiv.
[19] Duc-Cuong Dang,et al. Runtime Analysis of Non-elitist Populations: From Classical Optimisation to Partial Information , 2016, Algorithmica.
[20] Pietro Simone Oliveto,et al. Improved time complexity analysis of the Simple Genetic Algorithm , 2015, Theor. Comput. Sci..
[21] Carsten Witt,et al. (1+1) EA on Generalized Dynamic OneMax , 2015, FOGA.
[22] Marvin Künnemann,et al. Optimizing linear functions with the (1+λ) evolutionary algorithm - Different asymptotic runtimes for different instances , 2015, Theor. Comput. Sci..
[23] Timo Kötzing,et al. Robustness of Populations in Stochastic Environments , 2014, Algorithmica.
[24] Timo Kötzing,et al. Concentration of First Hitting Times Under Additive Drift , 2014, Algorithmica.
[25] Dirk Sudholt,et al. The choice of the offspring population size in the (1, λ) evolutionary algorithm , 2014, Theor. Comput. Sci..
[26] Benjamin Doerr,et al. Monotonic functions in EC: anything but monotone! , 2014, GECCO.
[27] Xiequan Fan,et al. Exponential inequalities for martingales with applications , 2013, 1311.6273.
[28] Mehryar Mohri,et al. Tight Lower Bound on the Probability of a Binomial Exceeding its Expectation , 2013, ArXiv.
[29] Per Kristian Lehre,et al. Fitness-levels for non-elitist populations , 2011, GECCO '11.
[30] L. A. Goldberg,et al. Adaptive Drift Analysis , 2010, Algorithmica.
[31] Benjamin Doerr,et al. Multiplicative Drift Analysis , 2010, GECCO '10.
[32] Daniel Johannsen,et al. Random combinatorial structures and randomized search heuristics , 2010 .
[33] Pietro Simone Oliveto,et al. Theoretical analysis of fitness-proportional selection: landscapes and efficiency , 2009, GECCO.
[34] Jonathan E. Rowe,et al. Theoretical analysis of local search strategies to optimize network communication subject to preserving the total number of links , 2009, Int. J. Intell. Comput. Cybern..
[35] Frank Neumann,et al. Rigorous analyses of fitness-proportional selection for optimizing linear functions , 2008, GECCO '08.
[36] Jonathan E. Rowe,et al. Preliminary theoretical analysis of a local search algorithm to optimize network communication subject to preserving the total number of links , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[37] Jens Jägersküpper,et al. Algorithmic analysis of a basic evolutionary algorithm for continuous optimization , 2007, Theor. Comput. Sci..
[38] Thomas Jansen,et al. On the brittleness of evolutionary algorithms , 2007, FOGA'07.
[39] Carsten Witt,et al. Runtime Analysis of the ( μ +1) EA on Simple Pseudo-Boolean Functions , 2006 .
[40] Carsten Witt,et al. Runtime Analysis of the ( + 1) EA on Simple Pseudo-Boolean Functions , 2006, Evolutionary Computation.
[41] Ali Esmaili,et al. Probability and Random Processes , 2005, Technometrics.
[42] Ingo Wegener,et al. On the Optimization of Monotone Polynomials by Simple Randomized Search Heuristics , 2005, Combinatorics, Probability and Computing.
[43] Eli Upfal,et al. Probability and Computing: Randomized Algorithms and Probabilistic Analysis , 2005 .
[44] Xin Yao,et al. A study of drift analysis for estimating computation time of evolutionary algorithms , 2004, Natural Computing.
[45] Ingo Wegener,et al. Theoretical Aspects of Evolutionary Algorithms , 2001, ICALP.
[46] Xin Yao,et al. Drift analysis and average time complexity of evolutionary algorithms , 2001, Artif. Intell..
[47] G. Grimmett,et al. Probability and random processes , 2002 .
[48] D. Freedman. On Tail Probabilities for Martingales , 1975 .
[49] A. Wald. On Cumulative Sums of Random Variables , 1944 .