Jannik Irmai
Doctoral Student
Research Interests
My research lies in discrete optimization and its applications in machine learning. This involves studying the complexity of combinatorial optimization problems. I am particularly interested in both the development of exact algorithms via polyhedral analysis and the development of efficient approximation algorithms.
Vita
Jannik obtained a Bachelor's degree in Mathematics from the Technical University Dortmund in 2017. In 2018, he spent a semester at the University of Jyväskylä, and in 2019 he did a one-year internship with GE Aviation. After that, he studied discrete optimization and optimization under uncertainty and obtained a Master's degree in Mathematics from the Technical University Dortmund in 2021.
Awards
Publications
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Irmai J., Zhao S., Presberger J. and Andres B.
A Graph Multi-separator Problem for Image Segmentation.
Journal of Mathematical Imaging and Vision (accepted)
@misc{irmai-2023-separator, author = {Jannik Irmai and Shengxian Zhao and Jannik Presberger and Bjoern Andres}, title = {A Graph Multi-separator Problem for Image Segmentation}, year = {2023}, eprint = {2307.04592}, archivePrefix = {arXiv}, url = {http://arxiv.org/abs/2307.04592}, }
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- Irmai J. and Andres B. A State-of-the-Art Cutting Plane Algorithm for Clique Partitioning. German Conference on Pattern Recognition (GCPR) 2024 (accepted)
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Naumann L. F., Irmai J., Zhao S. and Andres B.
Box Facets and Cut Facets of Lifted Multicut Polytopes.
International Conference on Machine Learning (ICML) 2024
@inproceedings{naumann-2024-cut, author = {Lucas Fabian Naumann and Jannik Irmai and Shengxian Zhao and Bjoern Andres}, title = {Box Facets and Cut Facets of Lifted Multicut Polytopes}, booktitle = {ICML}, year = {2024}, url = {https://proceedings.mlr.press/v235/naumann24a.html}, }
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Heidrich H., Irmai J. and Andres B.
A 4-Approximation Algorithm for Min Max Correlation Clustering.
International Conference on Artificial Intelligence and Statistics (AISTATS) 2024
@inproceedings{heidrich-2024, author = {Heidrich, Holger and Irmai, Jannik and Andres, Bjoern}, title = {A 4-Approximation Algorithm for Min Max Correlation Clustering}, booktitle = {AISTATS}, year = {2024}, url = {https://proceedings.mlr.press/v238/s-g-heidrich24a.html}, }
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Andres B., Di Gregorio S., Irmai J. and Lange J.-H.
A Polyhedral Study of Lifted Multicuts.
Discrete Optimization 47:100757, 2023
@article{andres-2023-a-polyhedral, author = {Bjoern Andres and Silvia {Di Gregorio} and Jannik Irmai and Jan-Hendrik Lange}, title = {A polyhedral study of lifted multicuts}, journal = {Discrete Optimization}, volume = {47}, pages = {100757}, year = {2023}, doi = {10.1016/j.disopt.2022.100757}, }
- Sekuboyina A., Irmai J., Shit S., Kirschke J., Andres B. and Menze B. H. Pushing the limits of an FCN and a CRF towards near-ideal vertebrae labelling. International Symposium on Biomedical Imaging (ISBI) 2023
- Buchheim C., Henke D. and Irmai J. The Stochastic Bilevel Continuous Knapsack Problem with Uncertain Follower's Objective. Journal of Optimization Theory and Applications 194(2):521-542, 2022
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Technical Reports
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Swoboda P., Andres B., Hornakova A., Bernard F., Irmai J., Roetzer P., Savchynskyy B., Stein D., Abbas A.
Structured Prediction Problem Archive.
arXiv 2024
@misc{swoboda-2024-structured, author = {Paul Swoboda and Bjoern Andres and Andrea Hornakova and Florian Bernard and Jannik Irmai and Paul Roetzer and Bogdan Savchynskyy and David Stein and Ahmed Abbas}, title = {Structured Prediction Problem Archive}, year = {2024}, eprint = {2202.03574}, archivePrefix = {arXiv}, url = {https://arxiv.org/abs/2202.03574}, }
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