# Ahmed Abbas (PhD Student)

## MSc Ahmed Abbas

Max-Planck-Institut für Informatik
Saarland Informatics Campus
Campus
Standort
-
Telefon
+49 681 9325 2000
Fax
+49 681 9325 2099

# Personal Information

### Research Interests:

• Optimization
• Computer Vision
• Machine Learning

### Previous positions:

• 2019 - 2020: Junior Scientist at Carl Zeiss AG, Germany
• 2013 - 2016: Research Engineer at LMKR, Pakistan

# Publications

Abbas, A. (2018). Bottleneck Potentials in Markov Random Fields. Universität des Saarlandes, Saarbrücken.
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BibTeX
@mastersthesis{Abbas_Master2019, TITLE = {Bottleneck Potentials in Markov Random Fields}, AUTHOR = {Abbas, Ahmed}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2018}, DATE = {2018}, }
Endnote
%0 Thesis %A Abbas, Ahmed %A referee: Schiele, Bernt %Y 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 Bottleneck Potentials in Markov Random Fields : %G eng %U http://hdl.handle.net/21.11116/0000-0003-9192-3 %I Universit&#228;t des Saarlandes %C Saarbr&#252;cken %D 2018 %P X, 57 p. %V master %9 master
Abbas, A., & Swoboda, P. (2019a). Bottleneck Potentials in Markov Random Fields. Retrieved from http://arxiv.org/abs/1904.08080
(arXiv: 1904.08080)
Abstract
We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment. Bottleneck potentials or analogous constructions have been considered in (i) combinatorial optimization (e.g. bottleneck shortest path problem, the minimum bottleneck spanning tree problem, bottleneck function minimization in greedoids), (ii) inverse problems with $L_{\infty}$-norm regularization, and (iii) valued constraint satisfaction on the $(\min,\max)$-pre-semirings. Bottleneck potentials for general discrete MRFs are a natural generalization of the above direction of modeling work to Maximum-A-Posteriori (MAP) inference in MRFs. To this end, we propose MRFs whose objective consists of two parts: terms that factorize according to (i) $(\min,+)$, i.e. potentials as in plain MRFs, and (ii) $(\min,\max)$, i.e. bottleneck potentials. To solve the ensuing inference problem, we propose high-quality relaxations and efficient algorithms for solving them. We empirically show efficacy of our approach on large scale seismic horizon tracking problems.
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BibTeX
@online{DBLP:journals/corr/abs-1904-08080, TITLE = {Bottleneck Potentials in {Markov Random Fields}}, AUTHOR = {Abbas, Ahmed and Swoboda, Paul}, LANGUAGE = {eng}, URL = {http://arxiv.org/abs/1904.08080}, EPRINT = {1904.08080}, EPRINTTYPE = {arXiv}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, ABSTRACT = {We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment. Bottleneck potentials or analogous constructions have been considered in (i) combinatorial optimization (e.g. bottleneck shortest path problem, the minimum bottleneck spanning tree problem, bottleneck function minimization in greedoids), (ii) inverse problems with $L_{\infty}$-norm regularization, and (iii) valued constraint satisfaction on the $(\min,\max)$-pre-semirings. Bottleneck potentials for general discrete MRFs are a natural generalization of the above direction of modeling work to Maximum-A-Posteriori (MAP) inference in MRFs. To this end, we propose MRFs whose objective consists of two parts: terms that factorize according to (i) $(\min,+)$, i.e. potentials as in plain MRFs, and (ii) $(\min,\max)$, i.e. bottleneck potentials. To solve the ensuing inference problem, we propose high-quality relaxations and efficient algorithms for solving them. We empirically show efficacy of our approach on large scale seismic horizon tracking problems.}, }
Endnote
%0 Report %A Abbas, Ahmed %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 %T Bottleneck Potentials in Markov Random Fields : %G eng %U http://hdl.handle.net/21.11116/0000-0003-9D88-3 %U http://arxiv.org/abs/1904.08080 %D 2019 %X We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment. Bottleneck potentials or analogous constructions have been considered in (i) combinatorial optimization (e.g. bottleneck shortest path problem, the minimum bottleneck spanning tree problem, bottleneck function minimization in greedoids), (ii) inverse problems with $L_{\infty}$-norm regularization, and (iii) valued constraint satisfaction on the $(\min,\max)$-pre-semirings. Bottleneck potentials for general discrete MRFs are a natural generalization of the above direction of modeling work to Maximum-A-Posteriori (MAP) inference in MRFs. To this end, we propose MRFs whose objective consists of two parts: terms that factorize according to (i) $(\min,+)$, i.e. potentials as in plain MRFs, and (ii) $(\min,\max)$, i.e. bottleneck potentials. To solve the ensuing inference problem, we propose high-quality relaxations and efficient algorithms for solving them. We empirically show efficacy of our approach on large scale seismic horizon tracking problems. %K Computer Science, Computer Vision and Pattern Recognition, cs.CV
Abbas, A., & Swoboda, P. (2019b). Bottleneck Potentials in Markov Random Fields. In International Conference on Computer Vision (ICCV 2019). Seoul, Korea: IEEE. doi:10.1109/ICCV.2019.00327
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@inproceedings{Abbas_ICCV2019, TITLE = {Bottleneck Potentials in {Markov Random Fields}}, AUTHOR = {Abbas, Ahmed and Swoboda, Paul}, LANGUAGE = {eng}, ISBN = {978-1-7281-4803-8}, DOI = {10.1109/ICCV.2019.00327}, PUBLISHER = {IEEE}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, DATE = {2019}, BOOKTITLE = {International Conference on Computer Vision (ICCV 2019)}, PAGES = {3174--3183}, ADDRESS = {Seoul, Korea}, }
Endnote
%0 Conference Proceedings %A Abbas, Ahmed %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 %T Bottleneck Potentials in Markov Random Fields : %G eng %U http://hdl.handle.net/21.11116/0000-0006-DC7E-6 %R 10.1109/ICCV.2019.00327 %D 2019 %B International Conference on Computer Vision %Z date of event: 2019-10-27 - 2019-11-02 %C Seoul, Korea %B International Conference on Computer Vision %P 3174 - 3183 %I IEEE %@ 978-1-7281-4803-8
Abbas, A., Nadeem, M., & Shafiq, A. (2014). Detection of Isotropic Regions and Enhancement of Fault Attributes in Seismic Volumes. SEG Technical Program Expanded Abstracts, 2014. doi:10.1190/segam2014-0425.1
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@article{Abbas2014, TITLE = {Detection of Isotropic Regions and Enhancement of Fault Attributes in Seismic Volumes}, AUTHOR = {Abbas, Ahmed and Nadeem, Mehak and Shafiq, Arsalan}, LANGUAGE = {eng}, ISSN = {1052-3812}, DOI = {10.1190/segam2014-0425.1}, PUBLISHER = {Society of Exploration Geophysicists}, YEAR = {2014}, DATE = {2014}, JOURNAL = {SEG Technical Program Expanded Abstracts}, VOLUME = {2014}, PAGES = {1420--1423}, }
Endnote
%0 Journal Article %A Abbas, Ahmed %A Nadeem, Mehak %A Shafiq, Arsalan %+ External Organizations External Organizations External Organizations %T Detection of Isotropic Regions and Enhancement of Fault Attributes in Seismic Volumes : %G eng %U http://hdl.handle.net/21.11116/0000-0007-1EF4-5 %R 10.1190/segam2014-0425.1 %7 2014 %D 2014 %J SEG Technical Program Expanded Abstracts %V 2014 %& 1420 %P 1420 - 1423 %I Society of Exploration Geophysicists %@ false
Abbas, A., Abbasi, H., & Shafiq, A. (2015). Enhancement of Subtle Features in Coherence Volumes. SEG Technical Program Expanded Abstracts, 2015. doi:10.1190/segam2015-5901251.1
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BibTeX
@article{Abbas2015, TITLE = {Enhancement of Subtle Features in Coherence Volumes}, AUTHOR = {Abbas, Ahmed and Abbasi, Hameer and Shafiq, Arsalan}, LANGUAGE = {eng}, ISSN = {1052-3812}, DOI = {10.1190/segam2015-5901251.1}, PUBLISHER = {Society of Exploration Geophysicists}, YEAR = {2015}, DATE = {2015}, JOURNAL = {SEG Technical Program Expanded Abstracts}, VOLUME = {2015}, PAGES = {1707--1710}, }
Endnote
%0 Journal Article %A Abbas, Ahmed %A Abbasi, Hameer %A Shafiq, Arsalan %+ External Organizations External Organizations External Organizations %T Enhancement of Subtle Features in Coherence Volumes : %G eng %U http://hdl.handle.net/21.11116/0000-0007-1EF1-8 %R 10.1190/segam2015-5901251.1 %7 2015 %D 2015 %J SEG Technical Program Expanded Abstracts %V 2015 %& 1707 %P 1707 - 1710 %I Society of Exploration Geophysicists %@ false