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ORCIDTimo Kötzing
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- affiliation: Hasso Plattner Institute, Potsdam, Germany
- affiliation: Friedrich Schiller University of Jena, Germany
- affiliation: Max Planck Institute for Informatics, Saarbrücken, Germany
- affiliation (PhD 2009): University of Delaware, Newark, DE, USA
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2020 – today
- 2024
[j37]Benjamin Doerr, Timo Kötzing:
Lower Bounds from Fitness Levels Made Easy. Algorithmica 86(2): 367-395 (2024)- [j36]Julian Berger, Maximilian Böther, Vanja Doskoc, Jonathan Gadea Harder, Nicolas Klodt, Timo Kötzing, Winfried Lötzsch, Jannik Peters, Leon Schiller, Lars Seifert, Armin Wells, Simon Wietheger:
Maps for learning indexable classes. Comput. 13(3-4): 237-261 (2024) - [c88]Jonathan Gadea Harder
, Timo Kötzing, Xiaoyue Li, Aishwarya Radhakrishnan, Janosch Ruff:
Run Time Bounds for Integer-Valued OneMax Functions. GECCO 2024 - [c87]Xiaoyue Li, Timo Kötzing:
Algorithm Performance Comparison for Integer-Valued OneMax. GECCO Companion 2024: 407-410 - [c86]Denis Antipov, Timo Kötzing, Aishwarya Radhakrishnan:
Greedy Versus Curious Parent Selection for Multi-objective Evolutionary Algorithms. PPSN (3) 2024: 86-101 - [i31]Timo Kötzing:
Theory of Stochastic Drift. CoRR abs/2406.14589 (2024) - 2023
- [j35]Tobias Friedrich, Timo Kötzing, Aishwarya Radhakrishnan, Leon Schiller, Martin Schirneck, Georg Tennigkeit, Simon Wietheger:
Crossover for Cardinality Constrained Optimization. ACM Trans. Evol. Learn. Optim. 3(2): 5:1-5:32 (2023) - [c85]Markus Wagner, Erik Kohlros, Gerome Quantmeyer, Timo Kötzing:
ELEA - Build your own Evolutionary Algorithm in your Browser. GECCO Companion 2023: 519-522 - [c84]Xiaoyue Li, Timo Kötzing:
Experimental Analyses of Crossover and Diversity on Jump. GECCO Companion 2023: 823-826 - [c83]Tobias Friedrich, Timo Kötzing, Aneta Neumann, Frank Neumann, Aishwarya Radhakrishnan:
Analysis of (1+1) EA on LeadingOnes with Constraints. GECCO 2023: 1584-1592 - [i30]Markus Wagner, Erik Kohlros, Gerome Quantmeyer, Timo Kötzing:
ELEA - Build your own Evolutionary Algorithm in your Browser. CoRR abs/2302.06277 (2023) - [i29]Tobias Friedrich, Timo Kötzing, Aneta Neumann, Frank Neumann, Aishwarya Radhakrishnan:
Analysis of the (1+1) EA on LeadingOnes with Constraints. CoRR abs/2305.18267 (2023) - [i28]Jonathan Gadea Harder, Timo Kötzing, Xiaoyue Li, Aishwarya Radhakrishnan:
Run Time Bounds for Integer-Valued OneMax Functions. CoRR abs/2307.11855 (2023) - 2022
- [c82]Vanja Doskoc, Timo Kötzing:
Maps of Restrictions for Behaviourally Correct Learning. CiE 2022: 103-114 - [c81]Samuel Baguley, Tobias Friedrich, Timo Kötzing, Xiaoyue Li, Marcus Pappik, Ziena Zeif:
Analysis of a gray-box operator for vertex cover. GECCO 2022: 1363-1371 - [c80]Tobias Friedrich, Timo Kötzing, Aishwarya Radhakrishnan, Leon Schiller, Martin Schirneck, Georg Tennigkeit, Simon Wietheger:
Crossover for cardinality constrained optimization. GECCO 2022: 1399-1407 - [c79]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Amirhossein Rajabi:
Escaping Local Optima with Local Search: A Theory-Driven Discussion. PPSN (2) 2022: 442-455 - [c78]Tobias Friedrich, Timo Kötzing, Frank Neumann, Aishwarya Radhakrishnan:
Theoretical Study of Optimizing Rugged Landscapes with the cGA. PPSN (2) 2022: 586-599 - [i27]Tobias Friedrich, Timo Kötzing, Frank Neumann, Aishwarya Radhakrishnan:
Theoretical Study of Optimizing Rugged Landscapes with the cGA. CoRR abs/2211.13801 (2022) - 2021
- [j34]Benjamin Doerr, Timo Kötzing:
Multiplicative Up-Drift. Algorithmica 83(10): 3017-3058 (2021) - [c77]Julian Berger, Maximilian Böther, Vanja Doskoc, Jonathan Gadea Harder, Nicolas Klodt, Timo Kötzing, Winfried Lötzsch, Jannik Peters, Leon Schiller, Lars Seifert, Armin Wells, Simon Wietheger:
Learning Languages with Decidable Hypotheses. CiE 2021: 25-37 - [c76]Vanja Doskoc, Timo Kötzing:
Mapping Monotonic Restrictions in Inductive Inference. CiE 2021: 146-157 - [c75]Vanja Doskoc, Timo Kötzing:
Normal Forms for Semantically Witness-Based Learners in Inductive Inference. CiE 2021: 158-168 - [c74]Ardalan Khazraei, Timo Kötzing, Karen Seidel:
Towards a Map for Incremental Learning in the Limit from Positive and Negative Information. CiE 2021: 273-284 - [c73]Timo Kötzing, Karen Seidel:
Learning Languages in the Limit from Positive Information with Finitely Many Memory Changes. CiE 2021: 318-329 - [c72]Benjamin Doerr, Timo Kötzing:
Lower bounds from fitness levels made easy. GECCO 2021: 1142-1150 - [i26]Benjamin Doerr, Timo Kötzing:
Lower Bounds from Fitness Levels Made Easy. CoRR abs/2104.03372 (2021) - 2020
- [j33]Feng Shi, Martin Schirneck, Tobias Friedrich, Timo Kötzing, Frank Neumann:
Correction to: Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints. Algorithmica 82(10): 3117-3123 (2020) - [j32]Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler, Anna Melnichenko:
Destructiveness of lexicographic parsimony pressure and alleviation by a concatenation crossover in genetic programming. Theor. Comput. Sci. 816: 96-113 (2020) - [j31]Benjamin Doerr, Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler:
The impact of lexicographic parsimony pressure for ORDER/MAJORITY on the run time. Theor. Comput. Sci. 816: 144-168 (2020) - [j30]Tobias Friedrich, Timo Kötzing, J. A. Gregor Lagodzinski, Frank Neumann, Martin Schirneck:
Analysis of the (1 + 1) EA on subclasses of linear functions under uniform and linear constraints. Theor. Comput. Sci. 832: 3-19 (2020) - [c71]Vanja Doskoc, Timo Kötzing:
Cautious Limit Learning. ALT 2020: 251-276 - [c70]Timo Kötzing, Carsten Witt:
Improved Fixed-Budget Results via Drift Analysis. PPSN (2) 2020: 648-660 - [i25]Timo Kötzing, Carsten Witt:
Improved Fixed-Budget Results via Drift Analysis. CoRR abs/2006.07019 (2020) - [i24]Ardalan Khazraei, Timo Kötzing, Karen Seidel:
Learning Half-Spaces and other Concept Classes in the Limit with Iterative Learners. CoRR abs/2010.03227 (2020) - [i23]Timo Kötzing, Karen Seidel:
Learning Languages in the Limit from Positive Information with Finitely Many Memory Changes. CoRR abs/2010.04782 (2020) - [i22]Julian Berger, Maximilian Böther, Vanja Doskoc, Jonathan Gadea Harder, Nicolas Klodt, Timo Kötzing, Winfried Lötzsch, Jannik Peters, Leon Schiller, Lars Seifert, Armin Wells, Simon Wietheger:
Maps for Learning Indexable Classes. CoRR abs/2010.09460 (2020) - [i21]Vanja Doskoc, Timo Kötzing:
Normal Forms for (Semantically) Witness-Based Learners in Inductive Inference. CoRR abs/2010.09461 (2020) - [i20]Vanja Doskoc, Timo Kötzing:
Mapping Monotonic Restrictions in Inductive Inference. CoRR abs/2010.09464 (2020) - [i19]Julian Berger, Maximilian Böther, Vanja Doskoc, Jonathan Gadea Harder, Nicolas Klodt, Timo Kötzing, Winfried Lötzsch, Jannik Peters, Leon Schiller, Lars Seifert, Armin Wells, Simon Wietheger:
Learning Languages with Decidable Hypotheses. CoRR abs/2011.09866 (2020)
2010 – 2019
- 2019
- [j29]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Solving Problems with Unknown Solution Length at Almost No Extra Cost. Algorithmica 81(2): 703-748 (2019) - [j28]Feng Shi, Martin Schirneck, Tobias Friedrich, Timo Kötzing, Frank Neumann:
Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints. Algorithmica 81(2): 828-857 (2019) - [j27]Benjamin Doerr, Philipp Fischbeck, Clemens Frahnow, Tobias Friedrich, Timo Kötzing, Martin Schirneck:
Island Models Meet Rumor Spreading. Algorithmica 81(2): 886-915 (2019) - [j26]Tobias Friedrich, Timo Kötzing, Martin S. Krejca:
Unbiasedness of estimation-of-distribution algorithms. Theor. Comput. Sci. 785: 46-59 (2019) - [j25]Timo Kötzing, Martin S. Krejca:
First-hitting times under drift. Theor. Comput. Sci. 796: 51-69 (2019) - [c69]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 - [c68]Ekaterina B. Fokina, Timo Kötzing, Luca San Mauro:
Limit Learning Equivalence Structures. ALT 2019: 383-403 - [c67]Benjamin Doerr, Timo Kötzing:
Multiplicative up-drift. GECCO 2019: 1470-1478 - [i18]Benjamin Doerr, Timo Kötzing:
Multiplicative Up-Drift. CoRR abs/1904.05682 (2019) - 2018
- [j24]Timo Kötzing, Dirk Sudholt:
Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. Algorithmica 80(5): 1575-1578 (2018) - [j23]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Static and Self-Adjusting Mutation Strengths for Multi-valued Decision Variables. Algorithmica 80(5): 1732-1768 (2018) - [j22]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) - [c66]Tobias Friedrich, Timo Kötzing, Francesco Quinzan, Andrew M. Sutton:
Improving the run time of the (1 + 1) evolutionary algorithm with luby sequences. GECCO 2018: 301-308 - [c65]Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler, Anna Melnichenko:
Destructiveness of Lexicographic Parsimony Pressure and Alleviation by a Concatenation Crossover in Genetic Programming. PPSN (2) 2018: 42-54 - [c64]Timo Kötzing, Martin S. Krejca:
First-Hitting Times for Finite State Spaces. PPSN (2) 2018: 79-91 - [c63]Timo Kötzing, Martin S. Krejca:
First-Hitting Times Under Additive Drift. PPSN (2) 2018: 92-104 - [c62]Clemens Frahnow, Timo Kötzing:
Ring Migration Topology Helps Bypassing Local Optima. PPSN (2) 2018: 129-140 - [i17]Martin Aschenbach, Timo Kötzing, Karen Seidel:
Learning Families of Formal Languages from Positive and Negative Information. CoRR abs/1801.10502 (2018) - [i16]Timo Kötzing, Martin S. Krejca:
First-Hitting Times Under Additive Drift. CoRR abs/1805.09415 (2018) - [i15]Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler, Anna Melnichenko:
Destructiveness of Lexicographic Parsimony Pressure and Alleviation by a Concatenation Crossover in Genetic Programming. CoRR abs/1805.10169 (2018) - [i14]Clemens Frahnow, Timo Kötzing:
Ring Migration Topology Helps Bypassing Local Optima. CoRR abs/1806.01128 (2018) - [i13]Andreas Göbel, Timo Kötzing, Martin S. Krejca:
Intuitive Analyses via Drift Theory. CoRR abs/1806.01919 (2018) - [i12]Benjamin Doerr, Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler:
Bounding Bloat in Genetic Programming. CoRR abs/1806.02112 (2018) - 2017
- [j21]Timo Kötzing:
A Solution to Wiehagen's Thesis. Theory Comput. Syst. 60(3): 498-520 (2017) - [j20]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) - [c61]Tobias Friedrich, Timo Kötzing, Markus Wagner:
A Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search. AAAI 2017: 801-807 - [c60]Timo Kötzing, Martin Schirneck, Karen Seidel:
Normal Forms in Semantic Language Identification. ALT 2017: 493-516 - [c59]Wanru Gao, Tobias Friedrich, Timo Kötzing, Frank Neumann:
Scaling up Local Search for Minimum Vertex Cover in Large Graphs by Parallel Kernelization. Australasian Conference on Artificial Intelligence 2017: 131-143 - [c58]Tobias Friedrich, Timo Kötzing, Francesco Quinzan, Andrew M. Sutton:
Resampling vs Recombination: a Statistical Run Time Estimation. FOGA 2017: 25-35 - [c57]Tobias Friedrich, Timo Kötzing, Gregor Lagodzinski, Frank Neumann, Martin Schirneck:
Analysis of the (1+1) EA on Subclasses of Linear Functions under Uniform and Linear Constraints. FOGA 2017: 45-54 - [c56]Tobias Friedrich, Timo Kötzing, Anna Melnichenko:
Analyzing search heuristics with differential equations. GECCO (Companion) 2017: 313-314 - [c55]Benjamin Doerr, Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler:
Bounding bloat in genetic programming. GECCO 2017: 921-928 - [c54]Benjamin Doerr, Philipp Fischbeck, Clemens Frahnow, Tobias Friedrich, Timo Kötzing, Martin Schirneck:
Island models meet rumor spreading. GECCO 2017: 1359-1366 - [c53]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unknown solution length problems with no asymptotically optimal run time. GECCO 2017: 1367-1374 - [c52]Feng Shi, Martin Schirneck, Tobias Friedrich, Timo Kötzing, Frank Neumann:
Reoptimization times of evolutionary algorithms on linear functions under dynamic uniform constraints. GECCO 2017: 1407-1414 - 2016
- [j19]Christian Gießen, Timo Kötzing:
Robustness of Populations in Stochastic Environments. Algorithmica 75(3): 462-489 (2016) - [j18]Timo Kötzing:
Concentration of First Hitting Times Under Additive Drift. Algorithmica 75(3): 490-506 (2016) - [j17]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
Robustness of Ant Colony Optimization to Noise. Evol. Comput. 24(2): 237-254 (2016) - [j16]Sanjay Jain, Timo Kötzing, Junqi Ma, Frank Stephan:
On the role of update constraints and text-types in iterative learning. Inf. Comput. 247: 152-168 (2016) - [j15]John Case, Timo Kötzing:
Strongly non-U-shaped language learning results by general techniques. Inf. Comput. 251: 1-15 (2016) - [j14]Sanjay Jain, Timo Kötzing, Frank Stephan:
Enlarging learnable classes. Inf. Comput. 251: 194-207 (2016) - [j13]John Case, Timo Kötzing:
Topological separations in inductive inference. Theor. Comput. Sci. 620: 33-45 (2016) - [j12]Timo Kötzing, Raphaela Palenta:
A map of update constraints in inductive inference. Theor. Comput. Sci. 650: 4-24 (2016) - [c51]Tobias Friedrich, Timo Kötzing, Francesco Quinzan, Andrew M. Sutton:
Ant Colony Optimization Beats Resampling on Noisy Functions. GECCO (Companion) 2016: 3-4 - [c50]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Benefit of Recombination in Noisy Evolutionary Search. GECCO (Companion) 2016: 161-162 - [c49]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 - [c48]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 - [c47]Benjamin Doerr, Carola Doerr, Timo Kötzing:
The Right Mutation Strength for Multi-Valued Decision Variables. GECCO 2016: 1115-1122 - [c46]Tobias Friedrich, Timo Kötzing, Martin S. Krejca:
EDAs cannot be Balanced and Stable. GECCO 2016: 1139-1146 - [c45]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
Graceful Scaling on Uniform Versus Steep-Tailed Noise. PPSN 2016: 761-770 - [c44]Tobias Friedrich, Timo Kötzing, Andrew M. Sutton:
On the Robustness of Evolving Populations. PPSN 2016: 771-781 - [c43]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Provably Optimal Self-adjusting Step Sizes for Multi-valued Decision Variables. PPSN 2016: 782-791 - [c42]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 - [c41]Timo Kötzing, Martin Schirneck:
Towards an Atlas of Computational Learning Theory. STACS 2016: 47:1-47:13 - [i11]Benjamin Doerr, Carola Doerr, Timo Kötzing:
The Right Mutation Strength for Multi-Valued Decision Variables. CoRR abs/1604.03277 (2016) - [i10]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) - [i9]Tobias Friedrich, Timo Kötzing, Markus Wagner:
A Generic Bet-and-run Strategy for Speeding Up Traveling Salesperson and Minimum Vertex Cover. CoRR abs/1609.03993 (2016) - 2015
- [j11]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unbiased Black-Box Complexities of Jump Functions. Evol. Comput. 23(4): 641-670 (2015) - [j10]Dominik D. Freydenberger, Timo Kötzing:
Fast Learning of Restricted Regular Expressions and DTDs. Theory Comput. Syst. 57(4): 1114-1158 (2015) - [c40]Timo Kötzing, Andrei Lissovoi, Carsten Witt:
(1+1) EA on Generalized Dynamic OneMax. FOGA 2015: 40-51 - [c39]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
Robustness of Ant Colony Optimization to Noise. GECCO 2015: 17-24 - [c38]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Solving Problems with Unknown Solution Length at (Almost) No Extra Cost. GECCO 2015: 831-838 - [c37]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Benefit of Recombination in Noisy Evolutionary Search. ISAAC 2015: 140-150 - [i8]Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Andrew M. Sutton:
The Benefit of Sex in Noisy Evolutionary Search. CoRR abs/1502.02793 (2015) - [i7]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Solving Problems with Unknown Solution Length at (Almost) No Extra Cost. CoRR abs/1506.05913 (2015) - 2014
- [j9]Benjamin Doerr, Carola Doerr, Timo Kötzing:
The unbiased black-box complexity of partition is polynomial. Artif. Intell. 216: 275-286 (2014) - [j8]Timo Kötzing:
Iterative learning from positive data and counters. Theor. Comput. Sci. 519: 155-169 (2014) - [j7]Timo Kötzing, Andrew M. Sutton, Frank Neumann, Una-May O'Reilly:
The Max problem revisited: The importance of mutation in genetic programming. Theor. Comput. Sci. 545: 94-107 (2014) - [c36]Timo Kötzing, Raphaela Palenta:
A Map of Update Constraints in Inductive Inference. ALT 2014: 40-54 - [c35]Sanjay Jain, Timo Kötzing, Junqi Ma, Frank Stephan:
On the Role of Update Constraints and Text-Types in Iterative Learning. ALT 2014: 55-69 - [c34]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unbiased black-box complexities of jump functions: how to cross large plateaus. GECCO 2014: 769-776 - [c33]Christian Gießen, Timo Kötzing:
Robustness of populations in stochastic environments. GECCO 2014: 1383-1390 - [c32]Timo Kötzing:
Concentration of first hitting times under additive drift. GECCO 2014: 1391-1398 - [c31]Timo Kötzing:
A Solution to Wiehagen's Thesis. STACS 2014: 494-505 - [i6]Benjamin Doerr, Carola Doerr, Timo Kötzing:
Unbiased Black-Box Complexities of Jump Functions - How to Cross Large Plateaus. CoRR abs/1403.7806 (2014) - [i5]Timo Kötzing, Raphaela Palenta:
A Map of Update Constraints in Inductive Inference. CoRR abs/1404.7527 (2014) - 2013
- [j6]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Frank Neumann, Madeleine Theile:
More effective crossover operators for the all-pairs shortest path problem. Theor. Comput. Sci. 471: 12-26 (2013) - [j5]Benjamin Doerr, Timo Kötzing, Johannes Lengler, Carola Winzen:
Black-box complexities of combinatorial problems. Theor. Comput. Sci. 471: 84-106 (2013) - [j4]John Case, Timo Kötzing:
Memory-limited non-U-shaped learning with solved open problems. Theor. Comput. Sci. 473: 100-123 (2013) - [c30]John Case, Timo Kötzing:
Topological Separations in Inductive Inference. ALT 2013: 128-142 - [c29]Matthias Feldmann, Timo Kötzing:
Optimizing expected path lengths with ant colony optimization using fitness proportional update. FOGA 2013: 65-74 - [c28]Florian Benz, Timo Kötzing:
An effective heuristic for the smallest grammar problem. GECCO 2013: 487-494 - [c27]Dominik D. Freydenberger, Timo Kötzing:
Fast learning of restricted regular expressions and DTDs. ICDT 2013: 45-56 - [c26]Cosmina Croitoru, Timo Kötzing:
A Normal Form for Argumentation Frameworks. TAFA 2013: 32-45 - [c25]Gilles Bailly, Antti Oulasvirta, Timo Kötzing, Sabrina Hoppe:
MenuOptimizer: interactive optimization of menu systems. UIST 2013: 331-342 - 2012
- [j3]John Case, Timo Kötzing:
Learning secrets interactively. Dynamic modeling in inductive inference. Inf. Comput. 220: 60-73 (2012) - [j2]Timo Kötzing, Frank Neumann, Heiko Röglin, Carsten Witt:
Theoretical analysis of two ACO approaches for the traveling salesman problem. Swarm Intell. 6(1): 1-21 (2012) - [j1]Jeffrey Heinz, Anna Kasprzik, Timo Kötzing:
Learning in the limit with lattice-structured hypothesis spaces. Theor. Comput. Sci. 457: 111-127 (2012) - [c24]Sanjay Jain, Timo Kötzing, Frank Stephan:
Enlarging Learnable Classes. ALT 2012: 36-50 - [c23]Benjamin Doerr, Ashish Ranjan Hota, Timo Kötzing:
Ants easily solve stochastic shortest path problems. GECCO 2012: 17-24 - [c22]Jan Baumbach, Tobias Friedrich, Timo Kötzing, Anton Krohmer, Joachim Müller, Josch Pauling:
Efficient algorithms for extracting biological key pathways with global constraints. GECCO 2012: 169-176 - [c21]Timo Kötzing, Andrew M. Sutton, Frank Neumann, Una-May O'Reilly:
The max problem revisited: the importance of mutation in genetic programming. GECCO 2012: 1333-1340 - [c20]Timo Kötzing, Hendrik Molter:
ACO Beats EA on a Dynamic Pseudo-Boolean Function. PPSN (1) 2012: 113-122 - [c19]Cosmina Croitoru, Timo Kötzing:
Deliberative Acceptability of Arguments. STAIRS 2012: 71-82 - [i4]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Frank Neumann, Madeleine Theile:
More Effective Crossover Operators for the All-Pairs Shortest Path Problem. CoRR abs/1207.0369 (2012) - 2011
- [c18]Timo Kötzing:
Iterative Learning from Positive Data and Counters. ALT 2011: 40-54 - [c17]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen:
Faster black-box algorithms through higher arity operators. FOGA 2011: 163-172 - [c16]Timo Kötzing, Frank Neumann, Dirk Sudholt, Markus Wagner:
Simple max-min ant systems and the optimization of linear pseudo-boolean functions. FOGA 2011: 209-218 - [c15]Benjamin Doerr, Johannes Lengler, Timo Kötzing, Carola Winzen:
Black-box complexities of combinatorial problems. GECCO 2011: 981-988 - [c14]Timo Kötzing, Dirk Sudholt, Madeleine Theile:
How crossover helps in pseudo-boolean optimization. GECCO 2011: 989-996 - [c13]Benjamin Doerr, Timo Kötzing, Carola Winzen:
Too fast unbiased black-box algorithms. GECCO 2011: 2043-2050 - [c12]Timo Kötzing, Frank Neumann, Reto Spöhel:
PAC learning and genetic programming. GECCO 2011: 2091-2096 - [c11]John Case, Timo Kötzing:
Measuring Learning Complexity with Criteria Epitomizers. STACS 2011: 320-331 - [i3]Benjamin Doerr, Timo Kötzing, Johannes Lengler, Carola Winzen:
Black-Box Complexities of Combinatorial Problems. CoRR abs/1108.0342 (2011) - 2010
- [c10]John Case, Timo Kötzing:
Solutions to Open Questions for Non-U-Shaped Learning with Memory Limitations. ALT 2010: 285-299 - [c9]Timo Kötzing, Frank Neumann, Heiko Röglin, Carsten Witt:
Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem. ANTS Conference 2010: 324-335 - [c8]John Case, Timo Kötzing:
Strongly Non-U-Shaped Learning Results by General Techniques. COLT 2010: 181-193 - [c7]Timo Kötzing, Per Kristian Lehre, Frank Neumann, Pietro S. Oliveto:
Ant colony optimization and the minimum cut problem. GECCO 2010: 1393-1400 - [c6]Anna Kasprzik, Timo Kötzing:
String Extension Learning Using Lattices. LATA 2010: 380-391 - [c5]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Frank Neumann, Madeleine Theile:
More Effective Crossover Operators for the All-Pairs Shortest Path Problem. PPSN (1) 2010: 184-193 - [i2]Timo Kötzing, Frank Neumann, Dirk Sudholt, Markus Wagner:
Simple Max-Min Ant Systems and the Optimization of Linear Pseudo-Boolean Functions. CoRR abs/1007.4707 (2010) - [i1]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen:
Faster Black-Box Algorithms Through Higher Arity Operators. CoRR abs/1012.0952 (2010)
2000 – 2009
- 2009
- [c4]John Case, Timo Kötzing:
Difficulties in Forcing Fairness of Polynomial Time Inductive Inference. ALT 2009: 263-277 - 2008
- [c3]John Case, Timo Kötzing:
Dynamically Delayed Postdictive Completeness and Consistency in Learning. ALT 2008: 389-403 - [c2]John Case, Timo Kötzing:
Dynamic Modeling in Inductive Inference. ALT 2008: 404-418 - 2007
- [c1]John Case, Timo Kötzing, Todd Paddock:
Feasible Iteration of Feasible Learning Functionals. ALT 2007: 34-48
Coauthor Index
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