Recent publications
Article
Lehre, PK & Qin, X 2022, 'More precise runtime analyses of non-elitist evolutionary algorithms in uncertain environments', Algorithmica. https://doi.org/10.1007/s00453-022-01044-5
Lehre, PK & Nguyen, H 2021, 'Runtime analyses of the population-based univariate estimation of distribution algorithms on LeadingOnes', Algorithmica, vol. 83, no. 10, pp. 3238-3280. https://doi.org/10.1007/s00453-021-00862-3
Case, B & Lehre, PK 2020, 'Self-adaptation in non-elitist evolutionary algorithms on discrete problems with unknown structure', IEEE Transactions on Evolutionary Computation, vol. 24, no. 4, 9056791, pp. 650-663. https://doi.org/10.1109/TEVC.2020.2985450
Lehre, PK & Witt, C 2020, 'Tail bounds on hitting times of randomized search heuristics using variable drift analysis', Combinatorics, Probability and Computing. https://doi.org/10.1017/S0963548320000565
Dang, D-C, Lehre, PK & Nguyen, PTH 2019, 'Level-based analysis of the univariate marginal distribution algorithm', Algorithmica, vol. 81, no. 2, pp. 668-702. https://doi.org/10.1007/s00453-018-0507-5
Lehre, PK & Sudholt, D 2019, 'Parallel black-box complexity with tail bounds', IEEE Transactions on Evolutionary Computation, pp. 1-15. https://doi.org/10.1109/TEVC.2019.2954234
Chapter (peer-reviewed)
Dang, D-C, Eremeev, AV & Lehre, PK 2020, Escaping Local Optima with Non-Elitist Evolutionary Algorithms. in Proceedings of AAAI 2021. AAAI Press.
Conference contribution
Dang, D-C, Eremeev, A, Lehre, PK & Qin, X 2022, Fast non-elitist evolutionary algorithms with power-law ranking selection. in JE Fieldsend (ed.), GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO: Genetic and Evolutionary Computation Conference, Association for Computing Machinery (ACM), New York, pp. 1372-1380, GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, United States, 9/07/22. https://doi.org/10.1145/3512290.3528873
Lehre, PK 2022, Runtime analysis of competitive co-evolutionary algorithms for maximin optimisation of a bilinear function. in JE Fieldsend (ed.), GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO: Genetic and Evolutionary Computation Conference, Association for Computing Machinery (ACM), New York, pp. 1408–1416, GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, United States, 9/07/22. https://doi.org/10.1145/3512290.3528853
Lehre, PK & Qin, X 2022, Self-adaptation via multi-objectivisation: a theoretical study. in JE Fieldsend (ed.), GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM), New York, pp. 1417-1425, GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, United States, 9/07/22. https://doi.org/10.1145/3512290.3528836
Qin, X & Lehre, PK 2022, Self-adaptation via multi-objectivisation: an empirical study. in G Rudolph, AV Kononova, H Aguirre, P Kerschke, G Ochoa & T Tušar (eds), Parallel Problem Solving from Nature – PPSN XVII: 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022, Proceedings, Part I. 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13398 LNCS, Springer, pp. 308–323, The seventeenth International Conference on Parallel Problem Solving from Nature, Dortmund, Germany, 10/09/22. https://doi.org/10.1007/978-3-031-14714-2_22
Lehre, PK & Qin, X 2021, More precise runtime analyses of non-elitist EAs in uncertain environments. in F Chicano (ed.), GECCO '21: Proceedings of the 2021 Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO), Association for Computing Machinery (ACM), New York, pp. 1160-1168, Genetic and Evolutionary Computation Conference, 10/07/21. https://doi.org/10.1145/3449639.3459312
Dang, D-C, Eremeev, A & Lehre, PK 2021, Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys. in F Chicano (ed.), GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO), Association for Computing Machinery (ACM), New York, pp. 1133–1141, 2021 Genetic and Evolutionary Computation Conference, GECCO 2021, Virtual, Online, France, 10/07/21. https://doi.org/10.1145/3449639.3459398
Lehre, PK & Nguyen, PTH 2019, On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help. in Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA '19). Association for Computing Machinery (ACM), New York, NY, USA, pp. 154-168, 15th ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV), Potsdam, Germany, 27/08/19. https://doi.org/10.1145/3299904.3340316
Lehre, PK & Nguyen, PTH 2019, Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise. in M López-Ibáñez (ed.), The Genetic and Evolutionary Computation Conference 2019 (GECCO 2019). GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference, Association for Computing Machinery (ACM), pp. 1497-1505, The Genetic and Evolutionary Computation Conference 2019 (GECCO 2019), Prague, Czech Republic, 13/07/19. https://doi.org/10.1145/3321707.3321834
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