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Sellmann, Meinolf
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1

Learning and Intelligent Optimization: 17th International C.. 

Lecture Notes in Computer Science, 14286
Sellmann, Meinolf ; Tierney, Kevin - 1st ed. 2023 . , 2023
Link: https://doi.org/10.1007/..
 
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2

The first AI4TSP competition: Learning to solve stochastic ..:

Zhang, Yingqian ; Bliek, Laurens ; da Costa, Paulo...
Artificial Intelligence.  319 (2023)  - p. 103918 , 2023
Link: https://doi.org/10.1016/..
 
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3

Learning to Solve a Stochastic Orienteering Problem with Ti..:

, In: Lecture Notes in Computer Science; Learning and Intelligent Optimization,
Schmitt-Ulms, Fynn ; Hottung, André ; Sellmann, Meinolf. - p. 108-122 , 2022
Link: https://doi.org/10.1007/..
 
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4

Modern hybrids - optimization using local search, populatio..:

, In: Proceedings of the Genetic and Evolutionary Computation Conference,
Sellmann, Meinolf - p. 1 ff. , 2022
Link: https://dl.acm.org/doi/1..
 
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5

Cost-sensitive Hierarchical Clustering for Dynamic Classifi..:

, In: 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA),
Sellmann, Meinolf ; Shah, Tapan - p. 782-787 , 2022
Link: https://doi.org/10.1109/..
 
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6

Learning to Optimize Black-Box Functions with Extreme Limit..:

, In: Lecture Notes in Computer Science; Learning and Intelligent Optimization,
Ansótegui, Carlos ; Sellmann, Meinolf ; Shah, Tapan. - p. 7-24 , 2021
Link: https://doi.org/10.1007/..
 
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7

PyDGGA: Distributed GGA for Automatic Configuration:

, In: Theory and Applications of Satisfiability Testing – SAT 2021; Lecture Notes in Computer Science,
Ansótegui, Carlos ; Pon, Josep ; Sellmann, Meinolf. - p. 11-20 , 2021
Link: https://doi.org/10.1007/..
 
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8

Boosting evolutionary algorithm configuration:

Ansótegui, Carlos ; Pon, Josep ; Sellmann, Meinolf
Annals of Mathematics and Artificial Intelligence.  90 (2021)  7-9 - p. 715-734 , 2021
Link: https://doi.org/10.1007/..
 
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9

Hyper-parameterized Dialectic Search for Non-linear Box-Con..:

, In: Lecture Notes in Computer Science; Learning and Intelligent Optimization,
Sellmann, Meinolf ; Tierney, Kevin - p. 102-116 , 2020
Link: https://doi.org/10.1007/..
 
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10

Empirical Confidence Models for Supervised Machine Learning:

, In: Advances in Artificial Intelligence; Lecture Notes in Computer Science,
Castro, Margarita P. ; Sellmann, Meinolf ; Yang, Zhaoyuan. - p. 105-117 , 2020
Link: https://doi.org/10.1007/..
 
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11

Exploiting Counterfactuals for Scalable Stochastic Optimiza..:

, In: Lecture Notes in Computer Science; Principles and Practice of Constraint Programming,
Kuhlemann, Stefan ; Sellmann, Meinolf ; Tierney, Kevin - p. 690-708 , 2019
Link: https://doi.org/10.1007/..
 
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12

Hyper-Reactive Tabu Search for MaxSAT:

, In: Lecture Notes in Computer Science; Learning and Intelligent Optimization,
Ansótegui, Carlos ; Heymann, Britta ; Pon, Josep.. - p. 309-325 , 2018
Link: https://doi.org/10.1007/..
 
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13

Self-configuring Cost-Sensitive Hierarchical Clustering wit..:

, In: Lecture Notes in Computer Science; Principles and Practice of Constraint Programming,
Ansotegui, Carlos ; Sellmann, Meinolf ; Tierney, Kevin - p. 524-534 , 2018
Link: https://doi.org/10.1007/..
 
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14

Meta-Algorithms in Cognitive Computing:

Sellmann, Meinolf
IEEE Intelligent Systems.  32 (2017)  4 - p. 35-39 , 2017
Link: https://doi.org/10.1109/..
 
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15

Learning and Intelligent Optimization 

10th International Conference, LION 10, Ischia, Italy, May ...  Lecture Notes in Computer Science ; 10079;Theoretical Computer Science and General Issues ; 10079;SpringerLink, Bücher;Springer eBook Collection, Computer Science
Sellmann, Meinolf ; Vanschoren, Joaquin ; Festa, Paola , 2016
Link: https://doi.org/10.1007/..
 
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