Machine Learning for Computer Vision Faculty of Computer Science TU Dresden
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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

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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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 (accepted) 
@misc{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},
    year = {2024},
    eprint = {2402.16814},
    archivePrefix = {arXiv},
    url = {https://arxiv.org/abs/2402.16814},
}
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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

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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