Jan-Hendrik Lange (PhD Student)

Personal Information

Research Interests:

Combinatorial Optimization
Applications of Mathematical Optimization in Machine Learning

Education:

Master of Science in Mathematics with Minor in Computer Science, Technische Universität Darmstadt, June 2016
Since June 2016: PhD Student at Max Planck Institute for Informatics

Publications

2025

Article

B. Andres, S. Di Gregorio, J. Irmai, and J.-H. Lange

“Corrigendum to ‘A polyhedral study of lifted multicuts’ [Discrete Optim. 47 (2023) 100757],” Discrete Optimization, vol. 55, 2025.

@article{Andres25,
TITLE = {Corrigendum to ``{A} polyhedral study of lifted multicuts'' [{Discrete Optim.} 47 (2023) 100757]},
AUTHOR = {Andres, Bjoern and Di Gregorio, Silvia and Irmai, Jannik and Lange, Jan-Hendrik},
LANGUAGE = {eng},
DOI = {10.1016/j.disopt.2024.100876},
PUBLISHER = {Elsevier},
ADDRESS = {Amsterdam},
YEAR = {2025},
MARGINALMARK = {$\bullet$},
DATE = {2025},
JOURNAL = {Discrete Optimization},
VOLUME = {55},
EID = {100876},
}

Endnote

%0 Journal Article
%A Andres, Bjoern
%A Di Gregorio, Silvia
%A Irmai, Jannik
%A Lange, Jan-Hendrik
%+ External Organizations
External Organizations
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Corrigendum to &#8220;A polyhedral study of lifted multicuts&#8221; [Discrete Optim. 47 (2023) 100757] : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0010-8BAF-D
%R 10.1016/j.disopt.2024.100876
%7 2025
%D 2025
%J Discrete Optimization
%V 55
%Z sequence number: 100876
%I Elsevier
%C Amsterdam

2023

Article

B. Andres, S. Di Gregorio, J. Irmai, and J.-H. Lange

“A Polyhedral Study of Lifted Multicuts,” Discrete Optimization, vol. 47, 2023.

@article{Andres23,
TITLE = {A Polyhedral Study of Lifted Multicuts},
AUTHOR = {Andres, Bjoern and Di Gregorio, Silvia and Irmai, Jannik and Lange, Jan-Hendrik},
LANGUAGE = {eng},
ISSN = {1572-5286},
DOI = {10.1016/j.disopt.2022.100757},
PUBLISHER = {Elsevier},
ADDRESS = {Amsterdam},
YEAR = {2023},
MARGINALMARK = {$\bullet$},
DATE = {2023},
JOURNAL = {Discrete Optimization},
VOLUME = {47},
EID = {100757},
}

Endnote

%0 Journal Article
%A Andres, Bjoern
%A Di Gregorio, Silvia
%A Irmai, Jannik
%A Lange, Jan-Hendrik
%+ External Organizations
External Organizations
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T A Polyhedral Study of Lifted Multicuts : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000C-C5ED-B
%R 10.1016/j.disopt.2022.100757
%7 2023
%D 2023
%J Discrete Optimization
%V 47
%Z sequence number: 100757
%I Elsevier
%C Amsterdam
%@ false

2021

Conference paper

J.-H. Lange and P. Swoboda

“Efficient Message Passing for 0–1 ILPs with Binary Decision Diagrams,” in Proceedings of the 38th International Conference on Machine Learning (ICML 2021), Virtual Event, 2021.

@inproceedings{Lange_ICML2021,
TITLE = {Efficient Message Passing for 0--1 {ILPs} with Binary Decision Diagrams},
AUTHOR = {Lange, Jan-Hendrik and Swoboda, Paul},
LANGUAGE = {eng},
PUBLISHER = {MLR Press},
YEAR = {2021},
BOOKTITLE = {Proceedings of the 38th International Conference on Machine Learning (ICML 2021)},
EDITOR = {Meila, Marina and Zhang, Tong},
PAGES = {6000--6010},
EID = {26},
SERIES = {Proceedings of the Machine Learning Research},
VOLUME = {139},
ADDRESS = {Virtual Event},
}

Endnote

%0 Conference Proceedings
%A Lange, Jan-Hendrik
%A Swoboda, Paul
%+ External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Efficient Message Passing for 0&#8211;1 ILPs with Binary Decision Diagrams : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0009-4A12-0
%D 2021
%B 38th International Conference on Machine Learning
%Z date of event: 2021-07-18 - 2021-07-24
%C Virtual Event
%B Proceedings of the 38th International Conference on Machine Learning
%E Meila, Marina; Zhang, Tong
%P 6000 - 6010
%Z sequence number: 26
%I MLR Press
%B Proceedings of the Machine Learning Research
%N 139

2020

Article

J.-H. Lange, M. E. Pfetsch, B. M.Seib, and A. M.Tillmann

“Sparse Recovery with Integrality Constraints,” Discrete Applied Mathematics, vol. 283, 2020.

@article{Lange2020,
TITLE = {Sparse Recovery with Integrality Constraints},
AUTHOR = {Lange, Jan-Hendrik and Pfetsch, Marc E. and M.Seib, Bianca and M.Tillmann, Andreas},
LANGUAGE = {eng},
ISSN = {0166-218X},
DOI = {10.1016/j.dam.2020.01.021},
PUBLISHER = {Elsevier},
ADDRESS = {Amsterdam},
YEAR = {2020},
DATE = {2020},
JOURNAL = {Discrete Applied Mathematics},
VOLUME = {283},
PAGES = {346--366},
}

Endnote

%0 Journal Article
%A Lange, Jan-Hendrik
%A Pfetsch, Marc E.
%A M.Seib, Bianca
%A M.Tillmann, Andreas
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
External Organizations
%T Sparse Recovery with Integrality Constraints : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0006-D31D-C
%R 10.1016/j.dam.2020.01.021
%7 2020
%D 2020
%J Discrete Applied Mathematics
%V 283
%& 346
%P 346 - 366
%I Elsevier
%C Amsterdam
%@ false

Conference paper

J.-H. Lange and B. Andres

“On the Lifted Multicut Polytope for Trees,” in Pattern Recognition (GCPR 2020), Tübingen, Germany, 2021.

@inproceedings{Lange2020c,
TITLE = {On the Lifted Multicut Polytope for Trees},
AUTHOR = {Lange, Jan-Hendrik and Andres, Bjoern},
LANGUAGE = {eng},
ISBN = {978-3-030-71277-8},
DOI = {10.1007/978-3-030-71278-5_26},
PUBLISHER = {Springer},
YEAR = {2020},
DATE = {2021},
BOOKTITLE = {Pattern Recognition (GCPR 2020)},
EDITOR = {Akata, Zeynep and Geiger, Andreas and Sattler, Torsten},
PAGES = {360--372},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {12544},
ADDRESS = {T{\"u}bingen, Germany},
}

Endnote

%0 Conference Proceedings
%A Lange, Jan-Hendrik
%A Andres, Bjoern
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T On the Lifted Multicut Polytope for Trees : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0006-EFB2-4
%R 10.1007/978-3-030-71278-5_26
%D 2021
%B 42nd German Conference on Pattern Recognition
%Z date of event: 2020-09-28 - 2020-10-01
%C T&#252;bingen, Germany
%B Pattern Recognition
%E Akata, Zeynep; Geiger, Andreas; Sattler, Torsten
%P 360 - 372
%I Springer
%@ 978-3-030-71277-8
%B Lecture Notes in Computer Science
%N 12544

Thesis

D2IMPR-CS

J.-H. Lange

“Multicut Optimization Guarantees & Geometry of Lifted Multicuts,” Universität des Saarlandes, Saarbrücken, 2020.

@phdthesis{Lange2020b,
TITLE = {Multicut Optimization Guarantees \& Geometry of Lifted Multicuts},
AUTHOR = {Lange, Jan-Hendrik},
LANGUAGE = {eng},
URL = {urn:nbn:de:bsz:291--ds-318138},
DOI = {10.22028/D291-31813},
SCHOOL = {Universit{\"a}t des Saarlandes},
ADDRESS = {Saarbr{\"u}cken},
YEAR = {2020},
DATE = {2020},
}

Endnote

%0 Thesis
%A Lange, Jan-Hendrik
%Y Andres, Bjoern
%A referee: Schiele, Bernt
%A referee: Werner, Tom&#225;&#353;
%A referee: Pock, Thomas
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
International Max Planck Research School, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
%T Multicut Optimization Guarantees & Geometry of Lifted Multicuts : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0006-EFE6-A
%R 10.22028/D291-31813
%U urn:nbn:de:bsz:291--ds-318138
%F OTHER: hdl:20.500.11880/29566
%I Universit&#228;t des Saarlandes
%C Saarbr&#252;cken
%D 2020
%P VIII, 117 p.
%V phd
%9 phd
%U http://dx.doi.org/10.22028/D291-31813

2019

Conference paper

J.-H. Lange, B. Andres, and P. Swoboda

“Combinatorial Persistency Criteria for Multicut and Max-Cut,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, USA, 2019.

@inproceedings{Lange2018c,
TITLE = {Combinatorial Persistency Criteria for Multicut and Max-Cut},
AUTHOR = {Lange, Jan-Hendrik and Andres, Bjoern and Swoboda, Paul},
LANGUAGE = {eng},
ISBN = {978-1-7281-3293-8},
DOI = {10.1109/CVPR.2019.00625},
PUBLISHER = {IEEE},
YEAR = {2019},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019)},
PAGES = {6086--6095},
ADDRESS = {Long Beach, CA, USA},
}

Endnote

%0 Conference Proceedings
%A Lange, Jan-Hendrik
%A Andres, Bjoern
%A Swoboda, Paul
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Combinatorial Persistency Criteria for Multicut and Max-Cut : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0002-A8E2-1
%R  10.1109/CVPR.2019.00625
%D 2019
%B 32nd IEEE Conference on Computer Vision and Pattern Recognition
%Z date of event: 2019-06-16 - 2019-06-20
%C Long Beach, CA, USA
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 6086 - 6095
%I IEEE
%@ 978-1-7281-3293-8

2018

Conference paper

E. Laude, J.-H. Lange, J. Schüpfer, C. Domokos, L. Leal-Taixé, F. R. Schmidt, B. Andres, and D. Cremers

“Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, UT, USA, 2018.

@inproceedings{Laude_2018_CVPR,
TITLE = {Discrete-Continuous {ADMM} for Transductive Inference in Higher-Order {MRF}s},
AUTHOR = {Laude, Emanuel and Lange, Jan-Hendrik and Sch{\"u}pfer, Jonas and Domokos, Csaba and Leal-Taix{\'e}, Laura and Schmidt, Frank R. and Andres, Bjoern and Cremers, Daniel},
LANGUAGE = {eng},
ISBN = {978-1-5386-6420-9},
DOI = {10.1109/CVPR.2018.00174},
PUBLISHER = {IEEE},
YEAR = {2018},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018)},
PAGES = {1614--1624},
ADDRESS = {Salt Lake City, UT, USA},
}

Endnote

%0 Conference Proceedings
%A Laude, Emanuel
%A Lange, Jan-Hendrik
%A Sch&#252;pfer, Jonas
%A Domokos, Csaba
%A Leal-Taix&#233;, Laura
%A Schmidt, Frank R.
%A Andres, Bjoern
%A Cremers, Daniel
%+ External Organizations
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
External Organizations
External Organizations
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
External Organizations
%T Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs : 
%G eng
%U http://hdl.handle.net/11858/00-001M-0000-002D-8B47-A
%R 10.1109/CVPR.2018.00174
%D 2018
%B 31st IEEE Conference on Computer Vision and Pattern Recognition 
%Z date of event: 2018-06-19 - 2018-06-21
%C Salt Lake City, UT, USA
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition 
%P 1614 - 1624
%I IEEE
%@ 978-1-5386-6420-9

Conference paper

D2D1

J.-H. Lange, A. Karrenbauer, and B. Andres

“Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering,” in Proceedings of the 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden, 2018.

@inproceedings{pmlr-v80-lange18a,
TITLE = {Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering},
AUTHOR = {Lange, Jan-Hendrik and Karrenbauer, Andreas and Andres, Bjoern},
LANGUAGE = {eng},
ISSN = {1938-7228},
URL = {http://proceedings.mlr.press/v80/lange18a.html},
PUBLISHER = {PMLR},
YEAR = {2018},
BOOKTITLE = {Proceedings of the 35th International Conference on Machine Learning (ICML 2018)},
EDITOR = {Dy, Jennifer and Krause, Andreas},
PAGES = {2898--2907},
SERIES = {Proceedings of Machine Learning Research},
VOLUME = {80},
ADDRESS = {Stockholm, Sweden},
}

Endnote

%0 Conference Proceedings
%A Lange, Jan-Hendrik
%A Karrenbauer, Andreas
%A Andres, Bjoern
%+ Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
Algorithms and Complexity, MPI for Informatics, Max Planck Society
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
%T Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0001-A71C-4
%U http://proceedings.mlr.press/v80/lange18a.html
%D 2018
%B 35th International Conference on Machine Learning
%Z date of event: 2018-07-10 - 2018-07-15
%C Stockholm, Sweden
%B Proceedings of the 35th International Conference on Machine Learning
%E Dy, Jennifer; Krause, Andreas
%P 2898 - 2907
%I PMLR
%B Proceedings of Machine Learning Research
%N 80
%@ false
%U http://proceedings.mlr.press/v80/lange18a/lange18a.pdf

2017

Conference paper

M. Rempfler, J.-H. Lange, F. Jug, C. Blasse, E. W. Myers, B. H. Menze, and B. Andres

“Efficient Algorithms for Moral Lineage Tracing,” in IEEE International Conference on Computer Vision (ICCV 2017), Venice, Italy, 2017.

@inproceedings{Rempfler_ICCV2017,
TITLE = {Efficient Algorithms for Moral Lineage Tracing},
AUTHOR = {Rempfler, Markus and Lange, Jan-Hendrik and Jug, Florian and Blasse, Corinna and Myers, Eugene W. and Menze, Bjoern H. and Andres, Bjoern},
LANGUAGE = {eng},
ISBN = {978-1-5386-1032-9},
DOI = {10.1109/ICCV.2017.503},
PUBLISHER = {IEEE},
YEAR = {2017},
DATE = {2017},
BOOKTITLE = {IEEE International Conference on Computer Vision (ICCV 2017)},
PAGES = {4705--4714},
ADDRESS = {Venice, Italy},
}

Endnote

%0 Conference Proceedings
%A Rempfler, Markus
%A Lange, Jan-Hendrik
%A Jug, Florian
%A Blasse, Corinna
%A Myers, Eugene W.
%A Menze, Bjoern H.
%A Andres, Bjoern
%+ External Organizations
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
External Organizations
External Organizations
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
%T Efficient Algorithms for Moral Lineage Tracing : 
%G eng
%U http://hdl.handle.net/11858/00-001M-0000-002C-7960-1
%R 10.1109/ICCV.2017.503
%D 2017
%B International Conference on Computer Vision
%Z date of event: 2017-10-22 - 2017-10-29
%C Venice, Italy
%B IEEE International Conference on Computer Vision 
%P 4705 - 4714
%I IEEE
%@ 978-1-5386-1032-9

Conference paper

A. Horňáková, J.-H. Lange, and B. Andres

“Analysis and Optimization of Graph Decompositions by Lifted Multicuts,” in Proceedings of the 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia, 2017.

@inproceedings{pmlr-v70-hornakova17a,
TITLE = {Analysis and Optimization of Graph Decompositions by Lifted Multicuts},
AUTHOR = {Hor{\v n}{\'a}kov{\'a}, Andrea and Lange, Jan-Hendrik and Andres, Bjoern},
LANGUAGE = {eng},
ISSN = {1938-7228},
URL = {http://proceedings.mlr.press/v70/hornakova17a.html},
YEAR = {2017},
BOOKTITLE = {Proceedings of the 34th International Conference on Machine Learning (ICML 2017)},
EDITOR = {Precup, Doina and Teh, Yee Whye},
PAGES = {1539--1548},
SERIES = {Proceedings of Machine Learning Research},
VOLUME = {70},
ADDRESS = {Sydney, Australia},
}

Endnote

%0 Conference Proceedings
%A Hor&#328;&#225;kov&#225;, Andrea
%A Lange, Jan-Hendrik
%A Andres, Bjoern
%+ Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society
%T Analysis and Optimization of Graph Decompositions by Lifted Multicuts : 
%G eng
%U http://hdl.handle.net/11858/00-001M-0000-002D-D59B-C
%U http://proceedings.mlr.press/v70/hornakova17a.html
%D 2017
%B 34th International Conference on Machine Learning
%Z date of event: 2017-08-06 - 2017-08-11
%C Sydney, Australia
%B Proceedings of the 34th International Conference on Machine Learning
%E Precup, Doina; Teh, Yee Whye
%P 1539 - 1548
%B Proceedings of Machine Learning Research
%N 70
%@ false
%U http://proceedings.mlr.press/v70/hornakova17a/hornakova17a.pdf

Jan-Hendrik Lange (PhD Student)

Personal Information

Publications

2025

BibTeX

Endnote

2023

BibTeX

Endnote

2021

BibTeX

Endnote

2020

BibTeX

Endnote

BibTeX

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2019

BibTeX

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2018

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2017

BibTeX

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