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ORCIDMartin S. Krejca
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- affiliation: Ecole Polytechnique, Palaiseau, France
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2020 – today
- 2024
[j17]Firas Ben Jedidia, Benjamin Doerr, Martin S. Krejca
:
Estimation-of-distribution algorithms for multi-valued decision variables. Theor. Comput. Sci. 1003: 114622 (2024)- [c35]Tobias Friedrich, Andreas Göbel, Nicolas Klodt, Martin S. Krejca, Marcus Pappik:
The Irrelevance of Influencers: Information Diffusion with Re-Activation and Immunity Lasts Exponentially Long on Social Network Models. AAAI 2024: 17389-17397 - [c34]Benjamin Doerr, Aymen Echarghaoui, Mohammed Jamal, Martin S. Krejca:
Runtime Analysis of the (μ + 1) GA: Provable Speed-Ups from Strong Drift towards Diverse Populations. AAAI 2024: 20683-20691 - [c33]Tobias Friedrich, Andreas Göbel, Nicolas Klodt, Martin S. Krejca, Marcus Pappik:
From Market Saturation to Social Reinforcement: Understanding the Impact of Non-Linearity in Information Diffusion Models. AAMAS 2024: 614-622 - [c32]Benjamin Doerr, Aymen Echarghaoui, Mohammed Jamal, Martin S. Krejca:
Runtime Analysis of the (μ + 1) GA: Provable Speed-Ups from Strong Drift towards Diverse Populations. GECCO Companion 2024: 35-36 - [c31]Benjamin Doerr, Martin S. Krejca, Nguyen Vu:
Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy Heuristics. GECCO 2024 - [c30]Martin S. Krejca, Carsten Witt:
A Flexible Evolutionary Algorithm with Dynamic Mutation Rate Archive. GECCO 2024 - [c29]Benjamin Doerr, Martin S. Krejca, Noé Weeks:
Proven Runtime Guarantees for How the MOEA/D: Computes the Pareto Front from the Subproblem Solutions. PPSN (3) 2024: 197-212 - [d1]Thomas Bläsius, Sarel Cohen, Philipp Fischbeck, Tobias Friedrich, Martin S. Krejca:
Robust Parameter Fitting to Realistic Network Models via Iterative Stochastic Approximation (Data and Code). Zenodo, 2024
- [i22]Thomas Bläsius, Sarel Cohen, Philipp Fischbeck, Tobias Friedrich, Martin S. Krejca:
Robust Parameter Fitting to Realistic Network Models via Iterative Stochastic Approximation. CoRR abs/2402.05534 (2024) - [i21]Martin S. Krejca, Carsten Witt:
A Flexible Evolutionary Algorithm With Dynamic Mutation Rate Archive. CoRR abs/2404.04015 (2024) - [i20]Benjamin Doerr, Martin S. Krejca, Nguyen Vu:
Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy Heuristics. CoRR abs/2404.04018 (2024) - [i19]Benjamin Doerr, Martin S. Krejca, Noé Weeks:
Proven Runtime Guarantees for How the MOEA/D Computes the Pareto Front From the Subproblem Solutions. CoRR abs/2405.01014 (2024) - 2023
- [j16]Thomas Bläsius, Tobias Friedrich, Martin S. Krejca, Louise Molitor:
The impact of geometry on monochrome regions in the flip Schelling process. Comput. Geom. 108: 101902 (2023) - [j15]Tobias Friedrich, Andreas Göbel, Martin S. Krejca, Marcus Pappik:
Polymer dynamics via cliques: New conditions for approximations. Theor. Comput. Sci. 942: 230-252 (2023) - [j14]Benjamin Doerr, Martin S. Krejca:
Bivariate estimation-of-distribution algorithms can find an exponential number of optima. Theor. Comput. Sci. 971: 114074 (2023) - [j13]Carola Doerr, Martin S. Krejca:
Run Time Analysis for Random Local Search on Generalized Majority Functions. IEEE Trans. Evol. Comput. 27(5): 1385-1397 (2023) - [j12]Maximilian Böther, Leon Schiller, Philipp Fischbeck, Louise Molitor, Martin S. Krejca, Tobias Friedrich:
Evolutionary Minimization of Traffic Congestion. IEEE Trans. Evol. Comput. 27(6): 1809-1821 (2023) - [c28]Firas Ben Jedidia, Benjamin Doerr, Martin S. Krejca:
Estimation-of-Distribution Algorithms for Multi-Valued Decision Variables. GECCO 2023: 230-238 - [c27]Sarel Cohen, Philipp Fischbeck, Tobias Friedrich, Martin S. Krejca:
The Common-Neighbors Metric Is Noise-Robust and Reveals Substructures of Real-World Networks. PAKDD (1) 2023: 67-79 - [i18]Benjamin Doerr, Aymen Echarghaoui, Mohammed Jamal, Martin S. Krejca:
Lasting Diversity and Superior Runtime Guarantees for the (μ+1) Genetic Algorithm. CoRR abs/2302.12570 (2023) - [i17]Firas Ben Jedidia, Benjamin Doerr, Martin S. Krejca:
Estimation-of-Distribution Algorithms for Multi-Valued Decision Variables. CoRR abs/2302.14420 (2023) - [i16]Benjamin Doerr, Martin S. Krejca:
Bivariate Estimation-of-Distribution Algorithms Can Find an Exponential Number of Optima. CoRR abs/2310.04042 (2023) - [i15]Diederick Vermetten, Martin S. Krejca, Marius Lindauer, Manuel López-Ibáñez, Katherine M. Malan:
Synergizing Theory and Practice of Automated Algorithm Design for Optimization (Dagstuhl Seminar 23332). Dagstuhl Reports 13(8): 46-70 (2023) - 2022
- [j11]Tobias Friedrich, Andreas Göbel, Martin S. Krejca, Marcus Pappik:
A Spectral Independence View on Hard Spheres via Block Dynamics. SIAM J. Discret. Math. 36(3): 2282-2322 (2022) - [c26]Tobias Friedrich, Andreas Göbel, Maximilian Katzmann, Martin S. Krejca, Marcus Pappik:
Algorithms for Hard-Constraint Point Processes via Discretization. COCOON 2022: 242-254 - [c25]André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr:
Theory-inspired parameter control benchmarks for dynamic algorithm configuration. GECCO 2022: 766-775 - [c24]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Amirhossein Rajabi:
Escaping Local Optima with Local Search: A Theory-Driven Discussion. PPSN (2) 2022: 442-455 - [c23]Sarel Cohen, Philipp Fischbeck, Tobias Friedrich, Martin S. Krejca, Thomas Sauerwald:
Accelerated Information Dissemination on Networks with Local and Global Edges. SIROCCO 2022: 79-97 - [i14]André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr:
Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration. CoRR abs/2202.03259 (2022) - [i13]Tobias Friedrich, Andreas Göbel, Maximilian Katzmann, Martin S. Krejca, Marcus Pappik:
Using random graphs to sample repulsive Gibbs point processes with arbitrary-range potentials. CoRR abs/2204.01793 (2022) - [i12]Carola Doerr, Martin S. Krejca:
Run Time Analysis for Random Local Search on Generalized Majority Functions. CoRR abs/2204.12770 (2022) - 2021
- [j10]Benjamin Doerr, Martin S. Krejca:
The Univariate Marginal Distribution Algorithm Copes Well with Deception and Epistasis. Evol. Comput. 29(4): 543-563 (2021) - [j9]Benjamin Doerr, Martin S. Krejca:
A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes. Theor. Comput. Sci. 851: 121-128 (2021) - [c22]Maximilian Böther, Leon Schiller, Philipp Fischbeck, Louise Molitor, Martin S. Krejca, Tobias Friedrich:
Evolutionary minimization of traffic congestion. GECCO 2021: 937-945 - [c21]Tobias Friedrich, Andreas Göbel, Martin S. Krejca, Marcus Pappik:
A Spectral Independence View on Hard Spheres via Block Dynamics. ICALP 2021: 66:1-66:15 - [c20]Thomas Bläsius, Tobias Friedrich, Martin S. Krejca, Louise Molitor:
The Impact of Geometry on Monochrome Regions in the Flip Schelling Process. ISAAC 2021: 29:1-29:17 - [i11]Thomas Bläsius, Tobias Friedrich, Martin S. Krejca, Louise Molitor:
The Flip Schelling Process on Random Geometric and Erdös-Rényi Graphs. CoRR abs/2102.09856 (2021) - [i10]Tobias Friedrich, Andreas Göbel, Maximilian Katzmann, Martin S. Krejca, Marcus Pappik:
Algorithms for general hard-constraint point processes via discretization. CoRR abs/2107.08848 (2021) - 2020
- [j8]Martin S. Krejca, Carsten Witt:
Lower bounds on the run time of the Univariate Marginal Distribution Algorithm on OneMax. Theor. Comput. Sci. 832: 143-165 (2020) - [j7]Benjamin Doerr, Martin S. Krejca:
Significance-Based Estimation-of-Distribution Algorithms. IEEE Trans. Evol. Comput. 24(6): 1025-1034 (2020) - [c19]Benjamin Doerr, Martin S. Krejca:
The Univariate Marginal Distribution Algorithm Copes Well with Deception and Epistasis. EvoCOP 2020: 51-66 - [c18]Benjamin Doerr, Martin S. Krejca:
The univariate marginal distribution algorithm copes well with deception and epistasis. GECCO Companion 2020: 17-18 - [c17]Benjamin Doerr, Martin S. Krejca:
Bivariate estimation-of-distribution algorithms can find an exponential number of optima. GECCO 2020: 796-804 - [c16]Tobias Friedrich, Martin S. Krejca, J. A. Gregor Lagodzinski, Manuel Rizzo, Arthur Zahn:
Memetic Genetic Algorithms for Time Series Compression by Piecewise Linear Approximation. ICONIP (3) 2020: 592-604 - [p1]Martin S. Krejca, Carsten Witt:
Theory of Estimation-of-Distribution Algorithms. Theory of Evolutionary Computation 2020: 405-442 - [i9]Benjamin Doerr, Martin S. Krejca:
A Simplified Run Time Analysis of the Univariate Marginal Distribution Algorithm on LeadingOnes. CoRR abs/2004.04978 (2020) - [i8]Benjamin Doerr, Martin S. Krejca:
The Univariate Marginal Distribution Algorithm Copes Well With Deception and Epistasis. CoRR abs/2007.08277 (2020) - [i7]Tobias Friedrich, Andreas Göbel, Martin S. Krejca, Marcus Pappik:
Polymer dynamics via cliques with applications to hard-sphere mixtures. CoRR abs/2007.08293 (2020)
2010 – 2019
- 2019
- [b1]Martin S. Krejca:
Theoretical analyses of univariate estimation-of-distribution algorithms. University of Potsdam, Germany, 2019 - [j6]Tobias Friedrich, Martin S. Krejca, Ralf Rothenberger, Tobias Arndt, Danijar Hafner, Thomas Kellermeier, Simon Krogmann, Armin Razmjou:
Routing for on-street parking search using probabilistic data. AI Commun. 32(2): 113-124 (2019) - [j5]Tobias Friedrich, Timo Kötzing, Martin S. Krejca:
Unbiasedness of estimation-of-distribution algorithms. Theor. Comput. Sci. 785: 46-59 (2019) - [j4]Timo Kötzing, Martin S. Krejca:
First-hitting times under drift. Theor. Comput. Sci. 796: 51-69 (2019) - [c15]Jannik Peters, Daniel Stephan, Isabel Amon, Hans Gawendowicz, Julius Lischeid, Lennart Salabarria, Jonas Umland, Felix Werner, Martin S. Krejca, Ralf Rothenberger, Timo Kötzing, Tobias Friedrich:
Mixed Integer Programming versus Evolutionary Computation for Optimizing a Hard Real-World Staff Assignment Problem. ICAPS 2019: 541-554 - 2018
- [j3]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Escaping Local Optima Using Crossover With Emergent Diversity. IEEE Trans. Evol. Comput. 22(3): 484-497 (2018) - [c14]Benjamin Doerr, Martin S. Krejca:
Significance-based estimation-of-distribution algorithms. GECCO 2018: 1483-1490 - [c13]Timo Kötzing, Martin S. Krejca:
First-Hitting Times for Finite State Spaces. PPSN (2) 2018: 79-91 - [c12]Timo Kötzing, Martin S. Krejca:
First-Hitting Times Under Additive Drift. PPSN (2) 2018: 92-104 - [c11]Thomas Bläsius, Jan Eube, Thomas Feldtkeller, Tobias Friedrich, Martin S. Krejca, J. A. Gregor Lagodzinski, Ralf Rothenberger, Julius Severin, Fabian Sommer, Justin Trautmann:
Memory-Restricted Routing with Tiled Map Data. SMC 2018: 3347-3354 - [i6]Timo Kötzing, Martin S. Krejca:
First-Hitting Times Under Additive Drift. CoRR abs/1805.09415 (2018) - [i5]Andreas Göbel, Timo Kötzing, Martin S. Krejca:
Intuitive Analyses via Drift Theory. CoRR abs/1806.01919 (2018) - [i4]Martin S. Krejca, Carsten Witt:
Theory of Estimation-of-Distribution Algorithms. CoRR abs/1806.05392 (2018) - [i3]Benjamin Doerr, Martin S. Krejca:
Significance-based Estimation-of-Distribution Algorithms. CoRR abs/1807.03495 (2018) - 2017
- [j2]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Compact Genetic Algorithm is Efficient Under Extreme Gaussian Noise. IEEE Trans. Evol. Comput. 21(3): 477-490 (2017) - [c10]Martin S. Krejca, Carsten Witt:
Lower Bounds on the Run Time of the Univariate Marginal Distribution Algorithm on OneMax. FOGA 2017: 65-79 - 2016
- [j1]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
Robustness of Ant Colony Optimization to Noise. Evol. Comput. 24(2): 237-254 (2016) - [c9]Tobias Arndt, Danijar Hafner, Thomas Kellermeier, Simon Krogmann, Armin Razmjou, Martin S. Krejca, Ralf Rothenberger, Tobias Friedrich:
Probabilistic Routing for On-Street Parking Search. ESA 2016: 6:1-6:13 - [c8]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Benefit of Recombination in Noisy Evolutionary Search. GECCO (Companion) 2016: 161-162 - [c7]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Escaping Local Optima with Diversity Mechanisms and Crossover. GECCO 2016: 645-652 - [c6]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Samadhi Nallaperuma, Frank Neumann, Martin Schirneck:
Fast Building Block Assembly by Majority Vote Crossover. GECCO 2016: 661-668 - [c5]Tobias Friedrich, Timo Kötzing, Martin S. Krejca:
EDAs cannot be Balanced and Stable. GECCO 2016: 1139-1146 - [c4]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
Graceful Scaling on Uniform Versus Steep-Tailed Noise. PPSN 2016: 761-770 - [c3]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms. PPSN 2016: 890-900 - [i2]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity. CoRR abs/1608.03123 (2016) - 2015
- [c2]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
Robustness of Ant Colony Optimization to Noise. GECCO 2015: 17-24 - [c1]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Benefit of Recombination in Noisy Evolutionary Search. ISAAC 2015: 140-150 - [i1]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Benefit of Sex in Noisy Evolutionary Search. CoRR abs/1502.02793 (2015)
Coauthor Index
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