Recent publications
Article
Case, B & Lehre, PK 2020, 'Self-adaptation in non-elitist evolutionary algorithms on discrete problems with unknown structure', IEEE Transactions on Evolutionary Computation. 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
Trubenová, B, Krejca, MS, Lehre, PK & Kötzing, T 2019, 'Surfing on the seascape: adaptation in a changing environment', Evolution; international journal of organic evolution, vol. 73, no. 7, pp. 1356-1374. https://doi.org/10.1111/evo.13784
Dang, D-C, Friedrich, T, Koetzing, T, Krejca, MS, Lehre, P, Oliveto, PS, Sudholt, D & Sutton, AM 2018, 'Escaping local optima using crossover with emergent diversity', IEEE Transactions on Evolutionary Computation, vol. 22, no. 3, pp. 484 - 497. https://doi.org/10.1109/TEVC.2017.2724201
Corus, D, Dang, D-C, Eremeev, AV & Lehre, PK 2018, 'Level-based analysis of genetic algorithms and other search processes', IEEE Transactions on Evolutionary Computation, vol. 22, no. 5, pp. 707 - 719. https://doi.org/10.1109/TEVC.2017.2753538
Corus, D & Lehre, PK 2018, 'Theory driven design of efficient genetic algorithms for a classical graph problem', Operations Research/ Computer Science Interfaces Series, vol. 62, pp. 125-140. https://doi.org/10.1007/978-3-319-58253-5_8
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
Lehre, PK & Qin, X 2021, More precise runtime analyses of non-elitist EAs in uncertain environments. in GECCO '21: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO), Association for Computing Machinery (ACM), Genetic and Evolutionary Computation Conference, 10/07/21.
Dang, D-C, Eremeev, A & Lehre, PK 2021, Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys. in GECCO '21: Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery (ACM), Genetic and Evolutionary Computation Conference, 10/07/21.
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
Lehre, PK & Nguyen, PTH 2018, Level-based analysis of the population-based incremental learning algorithm. in Proceedings of the 15th International Conference on Parallel Problem Solving from Nature 2018 (PPSN XV). 1 edn, vol. 11101, Lecture Notes in Computer Science, Springer, 15th International Conference on Parallel Problem Solving from Nature 2018 (PPSN XV), Coimbra, Portugal, 8/09/18. https://doi.org/10.1007/978-3-319-99253-2
Lehre, PK & Nguyen, PTH 2017, Improved runtime bounds for the univariate marginal distribution algorithm via anti-concentration. in GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery , pp. 1383-1390, GECCO 2017:, Berlin, Germany, 15/07/17. https://doi.org/10.1145/3071178.3071317
View all publications in research portal