---
_id: '34963'
author:
- first_name: A
full_name: Anonymous, A
last_name: Anonymous
citation:
ama: Anonymous A. Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference.;
2022.
apa: Anonymous, A. (2022). Cost of Privacy-preserving SMPC Protocols for NN-Based
Inference.
bibtex: '@book{Anonymous_2022, title={Cost of Privacy-preserving SMPC Protocols
for NN-Based Inference}, author={Anonymous, A}, year={2022} }'
chicago: Anonymous, A. Cost of Privacy-Preserving SMPC Protocols for NN-Based
Inference, 2022.
ieee: A. Anonymous, Cost of Privacy-preserving SMPC Protocols for NN-Based Inference.
2022.
mla: Anonymous, A. Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference.
2022.
short: A. Anonymous, Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference,
2022.
date_created: 2022-12-24T00:16:39Z
date_updated: 2023-01-10T10:31:49Z
department:
- _id: '34'
- _id: '64'
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
- _id: '13'
name: 'SFB 901 - C1: SFB 901 - Subproject C1'
status: public
supervisor:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
title: Cost of Privacy-preserving SMPC Protocols for NN-Based Inference
type: mastersthesis
user_id: '41047'
year: '2022'
...
---
_id: '35772'
author:
- first_name: Jan
full_name: Lohse, Jan
last_name: Lohse
citation:
ama: Lohse J. Lattice Revocation Mechanisms.; 2022.
apa: Lohse, J. (2022). Lattice Revocation Mechanisms.
bibtex: '@book{Lohse_2022, title={Lattice Revocation Mechanisms}, author={Lohse,
Jan}, year={2022} }'
chicago: Lohse, Jan. Lattice Revocation Mechanisms, 2022.
ieee: J. Lohse, Lattice Revocation Mechanisms. 2022.
mla: Lohse, Jan. Lattice Revocation Mechanisms. 2022.
short: J. Lohse, Lattice Revocation Mechanisms, 2022.
date_created: 2023-01-10T10:39:27Z
date_updated: 2023-01-10T11:54:43Z
department:
- _id: '64'
language:
- iso: eng
status: public
supervisor:
- first_name: Johannes
full_name: Blömer, Johannes
last_name: Blömer
title: Lattice Revocation Mechanisms
type: bachelorsthesis
user_id: '47434'
year: '2022'
...
---
_id: '36227'
author:
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Volker
full_name: Lohweg, Volker
last_name: Lohweg
- first_name: Alexander
full_name: Schneider, Alexander
last_name: Schneider
- first_name: Wolfram
full_name: Schenck, Wolfram
last_name: Schenck
- first_name: Ulrike
full_name: Kuhl, Ulrike
last_name: Kuhl
- first_name: Marco
full_name: Braun, Marco
last_name: Braun
- first_name: Anton
full_name: Pfeifer, Anton
last_name: Pfeifer
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
last_name: Holst
- first_name: Malte
full_name: Schmidt, Malte
last_name: Schmidt
- first_name: Gunnar
full_name: Schomaker, Gunnar
last_name: Schomaker
- first_name: Tanja
full_name: Tornede, Tanja
id: '40795'
last_name: Tornede
citation:
ama: 'Hammer B, Hüllermeier E, Lohweg V, et al. Schlussbericht ITS.ML: Intelligente
Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben
zur automatisierten Analyse von Daten mittels Maschinellen Lernens.; 2022.
doi:10.4119/unibi/2965622'
apa: 'Hammer, B., Hüllermeier, E., Lohweg, V., Schneider, A., Schenck, W., Kuhl,
U., Braun, M., Pfeifer, A., Holst, C.-A., Schmidt, M., Schomaker, G., & Tornede,
T. (2022). Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten
Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse
von Daten mittels Maschinellen Lernens. https://doi.org/10.4119/unibi/2965622'
bibtex: '@book{Hammer_Hüllermeier_Lohweg_Schneider_Schenck_Kuhl_Braun_Pfeifer_Holst_Schmidt_et
al._2022, title={Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten
Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse
von Daten mittels Maschinellen Lernens}, DOI={10.4119/unibi/2965622},
author={Hammer, Barbara and Hüllermeier, Eyke and Lohweg, Volker and Schneider,
Alexander and Schenck, Wolfram and Kuhl, Ulrike and Braun, Marco and Pfeifer,
Anton and Holst, Christoph-Alexander and Schmidt, Malte and et al.}, year={2022}
}'
chicago: 'Hammer, Barbara, Eyke Hüllermeier, Volker Lohweg, Alexander Schneider,
Wolfram Schenck, Ulrike Kuhl, Marco Braun, et al. Schlussbericht ITS.ML: Intelligente
Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben
zur automatisierten Analyse von Daten mittels Maschinellen Lernens, 2022.
https://doi.org/10.4119/unibi/2965622.'
ieee: 'B. Hammer et al., Schlussbericht ITS.ML: Intelligente Technische
Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben
zur automatisierten Analyse von Daten mittels Maschinellen Lernens. 2022.'
mla: 'Hammer, Barbara, et al. Schlussbericht ITS.ML: Intelligente Technische
Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben
zur automatisierten Analyse von Daten mittels Maschinellen Lernens. 2022,
doi:10.4119/unibi/2965622.'
short: 'B. Hammer, E. Hüllermeier, V. Lohweg, A. Schneider, W. Schenck, U. Kuhl,
M. Braun, A. Pfeifer, C.-A. Holst, M. Schmidt, G. Schomaker, T. Tornede, Schlussbericht
ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles
Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen
Lernens, 2022.'
date_created: 2023-01-11T15:00:00Z
date_updated: 2023-01-11T15:20:40Z
ddc:
- '004'
department:
- _id: '34'
- _id: '7'
- _id: '534'
doi: 10.4119/unibi/2965622
has_accepted_license: '1'
language:
- iso: ger
status: public
title: 'Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation
durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten
mittels Maschinellen Lernens'
type: report
user_id: '40795'
year: '2022'
...
---
_id: '27531'
abstract:
- lang: eng
text: "The Quantum Singular Value Transformation (QSVT) is a recent technique that\r\ngives
a unified framework to describe most quantum algorithms discovered so\r\nfar,
and may lead to the development of novel quantum algorithms. In this paper\r\nwe
investigate the hardness of classically simulating the QSVT. A recent result\r\nby
Chia, Gily\\'en, Li, Lin, Tang and Wang (STOC 2020) showed that the QSVT can\r\nbe
efficiently \"dequantized\" for low-rank matrices, and discussed its\r\nimplication
to quantum machine learning. In this work, motivated by\r\nestablishing the superiority
of quantum algorithms for quantum chemistry and\r\nmaking progress on the quantum
PCP conjecture, we focus on the other main class\r\nof matrices considered in
applications of the QSVT, sparse matrices.\r\n We first show how to efficiently
\"dequantize\", with arbitrarily small\r\nconstant precision, the QSVT associated
with a low-degree polynomial. We apply\r\nthis technique to design classical algorithms
that estimate, with constant\r\nprecision, the singular values of a sparse matrix.
We show in particular that a\r\ncentral computational problem considered by quantum
algorithms for quantum\r\nchemistry (estimating the ground state energy of a local
Hamiltonian when\r\ngiven, as an additional input, a state sufficiently close
to the ground state)\r\ncan be solved efficiently with constant precision on a
classical computer. As a\r\ncomplementary result, we prove that with inverse-polynomial
precision, the same\r\nproblem becomes BQP-complete. This gives theoretical evidence
for the\r\nsuperiority of quantum algorithms for chemistry, and strongly suggests
that\r\nsaid superiority stems from the improved precision achievable in the quantum\r\nsetting.
We also discuss how this dequantization technique may help make\r\nprogress on
the central quantum PCP conjecture."
author:
- first_name: Sevag
full_name: Gharibian, Sevag
id: '71541'
last_name: Gharibian
orcid: 0000-0002-9992-3379
- first_name: François Le
full_name: Gall, François Le
last_name: Gall
citation:
ama: 'Gharibian S, Gall FL. Dequantizing the Quantum Singular Value Transformation:
Hardness and Applications to Quantum Chemistry and the Quantum PCP Conjecture.
In: Proceedings of the 54th ACM Symposium on Theory of Computing (STOC).
; 2022:19-32.'
apa: 'Gharibian, S., & Gall, F. L. (2022). Dequantizing the Quantum Singular
Value Transformation: Hardness and Applications to Quantum Chemistry and the
Quantum PCP Conjecture. Proceedings of the 54th ACM Symposium on Theory of
Computing (STOC), 19–32.'
bibtex: '@inproceedings{Gharibian_Gall_2022, title={Dequantizing the Quantum Singular
Value Transformation: Hardness and Applications to Quantum Chemistry and the
Quantum PCP Conjecture}, booktitle={Proceedings of the 54th ACM Symposium on Theory
of Computing (STOC)}, author={Gharibian, Sevag and Gall, François Le}, year={2022},
pages={19–32} }'
chicago: 'Gharibian, Sevag, and François Le Gall. “Dequantizing the Quantum Singular
Value Transformation: Hardness and Applications to Quantum Chemistry and the
Quantum PCP Conjecture.” In Proceedings of the 54th ACM Symposium on Theory
of Computing (STOC), 19–32, 2022.'
ieee: 'S. Gharibian and F. L. Gall, “Dequantizing the Quantum Singular Value Transformation:
Hardness and Applications to Quantum Chemistry and the Quantum PCP Conjecture,”
in Proceedings of the 54th ACM Symposium on Theory of Computing (STOC),
2022, pp. 19–32.'
mla: 'Gharibian, Sevag, and François Le Gall. “Dequantizing the Quantum Singular
Value Transformation: Hardness and Applications to Quantum Chemistry and the
Quantum PCP Conjecture.” Proceedings of the 54th ACM Symposium on Theory of
Computing (STOC), 2022, pp. 19–32.'
short: 'S. Gharibian, F.L. Gall, in: Proceedings of the 54th ACM Symposium on Theory
of Computing (STOC), 2022, pp. 19–32.'
date_created: 2021-11-18T07:32:56Z
date_updated: 2023-10-09T04:17:29Z
department:
- _id: '623'
- _id: '7'
external_id:
arxiv:
- '2111.09079'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2111.09079
oa: '1'
page: 19-32
publication: Proceedings of the 54th ACM Symposium on Theory of Computing (STOC)
publication_status: published
status: public
title: 'Dequantizing the Quantum Singular Value Transformation: Hardness and Applications
to Quantum Chemistry and the Quantum PCP Conjecture'
type: conference
user_id: '71541'
year: '2022'
...
---
_id: '46300'
author:
- first_name: Marco
full_name: Niemann, Marco
last_name: Niemann
- first_name: Dennis
full_name: Assenmacher, Dennis
last_name: Assenmacher
- first_name: Jens
full_name: Brunk, Jens
last_name: Brunk
- first_name: Dennis Maximilian
full_name: Riehle, Dennis Maximilian
last_name: Riehle
- first_name: Jörg
full_name: Becker, Jörg
last_name: Becker
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Niemann M, Assenmacher D, Brunk J, Riehle DM, Becker J, Trautmann H. (Semi-)Automatische
Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In: Weitzel G, Mündges
S, eds. Hate Speech — Definitionen, Ausprägungen, Lösungen. VS Verlag für
Sozialwissenschaften; 2022:249–274. doi:10.1007/978-3-658-35658-3_13'
apa: Niemann, M., Assenmacher, D., Brunk, J., Riehle, D. M., Becker, J., & Trautmann,
H. (2022). (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver
Diskurse. In G. Weitzel & S. Mündges (Eds.), Hate Speech — Definitionen,
Ausprägungen, Lösungen (pp. 249–274). VS Verlag für Sozialwissenschaften.
https://doi.org/10.1007/978-3-658-35658-3_13
bibtex: '@inbook{Niemann_Assenmacher_Brunk_Riehle_Becker_Trautmann_2022, place={Wiesbaden},
title={(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse},
DOI={10.1007/978-3-658-35658-3_13},
booktitle={Hate Speech — Definitionen, Ausprägungen, Lösungen}, publisher={VS
Verlag für Sozialwissenschaften}, author={Niemann, Marco and Assenmacher, Dennis
and Brunk, Jens and Riehle, Dennis Maximilian and Becker, Jörg and Trautmann,
Heike}, editor={Weitzel, Gerrit and Mündges, Stephan}, year={2022}, pages={249–274}
}'
chicago: 'Niemann, Marco, Dennis Assenmacher, Jens Brunk, Dennis Maximilian Riehle,
Jörg Becker, and Heike Trautmann. “(Semi-)Automatische Kommentarmoderation Zur
Erhaltung Konstruktiver Diskurse.” In Hate Speech — Definitionen, Ausprägungen,
Lösungen, edited by Gerrit Weitzel and Stephan Mündges, 249–274. Wiesbaden:
VS Verlag für Sozialwissenschaften, 2022. https://doi.org/10.1007/978-3-658-35658-3_13.'
ieee: 'M. Niemann, D. Assenmacher, J. Brunk, D. M. Riehle, J. Becker, and H. Trautmann,
“(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse,”
in Hate Speech — Definitionen, Ausprägungen, Lösungen, G. Weitzel and S.
Mündges, Eds. Wiesbaden: VS Verlag für Sozialwissenschaften, 2022, pp. 249–274.'
mla: Niemann, Marco, et al. “(Semi-)Automatische Kommentarmoderation Zur Erhaltung
Konstruktiver Diskurse.” Hate Speech — Definitionen, Ausprägungen, Lösungen,
edited by Gerrit Weitzel and Stephan Mündges, VS Verlag für Sozialwissenschaften,
2022, pp. 249–274, doi:10.1007/978-3-658-35658-3_13.
short: 'M. Niemann, D. Assenmacher, J. Brunk, D.M. Riehle, J. Becker, H. Trautmann,
in: G. Weitzel, S. Mündges (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen,
VS Verlag für Sozialwissenschaften, Wiesbaden, 2022, pp. 249–274.'
date_created: 2023-08-04T07:03:47Z
date_updated: 2023-10-16T12:35:41Z
department:
- _id: '819'
- _id: '34'
doi: 10.1007/978-3-658-35658-3_13
editor:
- first_name: Gerrit
full_name: Weitzel, Gerrit
last_name: Weitzel
- first_name: Stephan
full_name: Mündges, Stephan
last_name: Mündges
language:
- iso: eng
page: 249–274
place: Wiesbaden
publication: Hate Speech — Definitionen, Ausprägungen, Lösungen
publication_identifier:
isbn:
- 978-3-658-35658-3
publisher: VS Verlag für Sozialwissenschaften
status: public
title: (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse
type: book_chapter
user_id: '15504'
year: '2022'
...
---
_id: '46301'
author:
- first_name: D
full_name: Assenmacher, D
last_name: Assenmacher
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Assenmacher D, Trautmann H. Textual One-Pass Stream Clustering with Automated
Distance Threshold Adaption. In: et al. Tran T, ed. Intelligent Information
and Database Systems. Springer International Publishing; 2022:3–16. doi:10.1007/978-3-031-21743-2_1'
apa: Assenmacher, D., & Trautmann, H. (2022). Textual One-Pass Stream Clustering
with Automated Distance Threshold Adaption. In T. et al. Tran (Ed.), Intelligent
Information and Database Systems (pp. 3–16). Springer International Publishing.
https://doi.org/10.1007/978-3-031-21743-2_1
bibtex: '@inproceedings{Assenmacher_Trautmann_2022, place={Cham}, title={Textual
One-Pass Stream Clustering with Automated Distance Threshold Adaption}, DOI={10.1007/978-3-031-21743-2_1},
booktitle={Intelligent Information and Database Systems}, publisher={Springer
International Publishing}, author={Assenmacher, D and Trautmann, Heike}, editor={et
al. Tran, T}, year={2022}, pages={3–16} }'
chicago: 'Assenmacher, D, and Heike Trautmann. “Textual One-Pass Stream Clustering
with Automated Distance Threshold Adaption.” In Intelligent Information and
Database Systems, edited by T et al. Tran, 3–16. Cham: Springer International
Publishing, 2022. https://doi.org/10.1007/978-3-031-21743-2_1.'
ieee: 'D. Assenmacher and H. Trautmann, “Textual One-Pass Stream Clustering with
Automated Distance Threshold Adaption,” in Intelligent Information and Database
Systems, 2022, pp. 3–16, doi: 10.1007/978-3-031-21743-2_1.'
mla: Assenmacher, D., and Heike Trautmann. “Textual One-Pass Stream Clustering with
Automated Distance Threshold Adaption.” Intelligent Information and Database
Systems, edited by T et al. Tran, Springer International Publishing, 2022,
pp. 3–16, doi:10.1007/978-3-031-21743-2_1.
short: 'D. Assenmacher, H. Trautmann, in: T. et al. Tran (Ed.), Intelligent Information
and Database Systems, Springer International Publishing, Cham, 2022, pp. 3–16.'
date_created: 2023-08-04T07:04:54Z
date_updated: 2023-10-16T12:35:22Z
department:
- _id: '819'
- _id: '34'
doi: 10.1007/978-3-031-21743-2_1
editor:
- first_name: T
full_name: et al. Tran, T
last_name: et al. Tran
language:
- iso: eng
page: 3–16
place: Cham
publication: Intelligent Information and Database Systems
publisher: Springer International Publishing
status: public
title: Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '46316'
abstract:
- lang: eng
text: ' Computational social science uses computational and statistical methods
in order to evaluate social interaction. The public availability of data sets
is thus a necessary precondition for reliable and replicable research. These data
allow researchers to benchmark the computational methods they develop, test the
generalizability of their findings, and build confidence in their results. When
social media data are concerned, data sharing is often restricted for legal or
privacy reasons, which makes the comparison of methods and the replicability of
research results infeasible. Social media analytics research, consequently, faces
an integrity crisis. How is it possible to create trust in computational or statistical
analyses, when they cannot be validated by third parties? In this work, we explore
this well-known, yet little discussed, problem for social media analytics. We
investigate how this problem can be solved by looking at related computational
research areas. Moreover, we propose and implement a prototype to address the
problem in the form of a new evaluation framework that enables the comparison
of algorithms without the need to exchange data directly, while maintaining flexibility
for the algorithm design. '
author:
- first_name: Dennis
full_name: Assenmacher, Dennis
last_name: Assenmacher
- first_name: Derek
full_name: Weber, Derek
last_name: Weber
- first_name: Mike
full_name: Preuss, Mike
last_name: Preuss
- first_name: André Calero
full_name: Valdez, André Calero
last_name: Valdez
- first_name: Alison
full_name: Bradshaw, Alison
last_name: Bradshaw
- first_name: Björn
full_name: Ross, Björn
last_name: Ross
- first_name: Stefano
full_name: Cresci, Stefano
last_name: Cresci
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
citation:
ama: 'Assenmacher D, Weber D, Preuss M, et al. Benchmarking Crisis in Social Media
Analytics: A Solution for the Data-Sharing Problem. Social Science Computer
Review. 2022;40(6):1496-1522. doi:10.1177/08944393211012268'
apa: 'Assenmacher, D., Weber, D., Preuss, M., Valdez, A. C., Bradshaw, A., Ross,
B., Cresci, S., Trautmann, H., Neumann, F., & Grimme, C. (2022). Benchmarking
Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social
Science Computer Review, 40(6), 1496–1522. https://doi.org/10.1177/08944393211012268'
bibtex: '@article{Assenmacher_Weber_Preuss_Valdez_Bradshaw_Ross_Cresci_Trautmann_Neumann_Grimme_2022,
title={Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing
Problem}, volume={40}, DOI={10.1177/08944393211012268},
number={6}, journal={Social Science Computer Review}, author={Assenmacher, Dennis
and Weber, Derek and Preuss, Mike and Valdez, André Calero and Bradshaw, Alison
and Ross, Björn and Cresci, Stefano and Trautmann, Heike and Neumann, Frank and
Grimme, Christian}, year={2022}, pages={1496–1522} }'
chicago: 'Assenmacher, Dennis, Derek Weber, Mike Preuss, André Calero Valdez, Alison
Bradshaw, Björn Ross, Stefano Cresci, Heike Trautmann, Frank Neumann, and Christian
Grimme. “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing
Problem.” Social Science Computer Review 40, no. 6 (2022): 1496–1522. https://doi.org/10.1177/08944393211012268.'
ieee: 'D. Assenmacher et al., “Benchmarking Crisis in Social Media Analytics:
A Solution for the Data-Sharing Problem,” Social Science Computer Review,
vol. 40, no. 6, pp. 1496–1522, 2022, doi: 10.1177/08944393211012268.'
mla: 'Assenmacher, Dennis, et al. “Benchmarking Crisis in Social Media Analytics:
A Solution for the Data-Sharing Problem.” Social Science Computer Review,
vol. 40, no. 6, 2022, pp. 1496–522, doi:10.1177/08944393211012268.'
short: D. Assenmacher, D. Weber, M. Preuss, A.C. Valdez, A. Bradshaw, B. Ross, S.
Cresci, H. Trautmann, F. Neumann, C. Grimme, Social Science Computer Review 40
(2022) 1496–1522.
date_created: 2023-08-04T07:26:36Z
date_updated: 2023-10-16T12:57:24Z
department:
- _id: '34'
- _id: '819'
doi: 10.1177/08944393211012268
intvolume: ' 40'
issue: '6'
language:
- iso: eng
page: 1496-1522
publication: Social Science Computer Review
status: public
title: 'Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing
Problem'
type: journal_article
user_id: '15504'
volume: 40
year: '2022'
...
---
_id: '33957'
abstract:
- lang: eng
text: Manufacturing companies are challenged to make the increasingly complex work
processes equally manageable for all employees to prevent an impending loss of
competence. In this contribution, an intelligent assistance system is proposed
enabling employees to help themselves in the workplace and provide them with competence-related
support. This results in increasing the short- and long-term efficiency of problem
solving in companies.
author:
- first_name: Sahar
full_name: Deppe, Sahar
last_name: Deppe
- first_name: Lukas
full_name: Brandt, Lukas
last_name: Brandt
- first_name: Marc
full_name: Brünninghaus, Marc
last_name: Brünninghaus
- first_name: Jörg
full_name: Papenkordt, Jörg
id: '44648'
last_name: Papenkordt
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Gudrun
full_name: Tschirner-Vinke, Gudrun
last_name: Tschirner-Vinke
citation:
ama: Deppe S, Brandt L, Brünninghaus M, Papenkordt J, Heindorf S, Tschirner-Vinke
G. AI-Based Assistance System for Manufacturing. Published online 2022. doi:10.1109/ETFA52439.2022.9921520
apa: Deppe, S., Brandt, L., Brünninghaus, M., Papenkordt, J., Heindorf, S., &
Tschirner-Vinke, G. (2022). AI-Based Assistance System for Manufacturing.
ETFA, Stuttgart. https://doi.org/10.1109/ETFA52439.2022.9921520
bibtex: '@article{Deppe_Brandt_Brünninghaus_Papenkordt_Heindorf_Tschirner-Vinke_2022,
series={2022 IEEE 27th International Conference on Emerging Technologies and Factory
Automation (ETFA)}, title={AI-Based Assistance System for Manufacturing}, DOI={10.1109/ETFA52439.2022.9921520},
author={Deppe, Sahar and Brandt, Lukas and Brünninghaus, Marc and Papenkordt,
Jörg and Heindorf, Stefan and Tschirner-Vinke, Gudrun}, year={2022}, collection={2022
IEEE 27th International Conference on Emerging Technologies and Factory Automation
(ETFA)} }'
chicago: Deppe, Sahar, Lukas Brandt, Marc Brünninghaus, Jörg Papenkordt, Stefan
Heindorf, and Gudrun Tschirner-Vinke. “AI-Based Assistance System for Manufacturing.”
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation
(ETFA), 2022. https://doi.org/10.1109/ETFA52439.2022.9921520.
ieee: 'S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, and G.
Tschirner-Vinke, “AI-Based Assistance System for Manufacturing.” 2022, doi: 10.1109/ETFA52439.2022.9921520.'
mla: Deppe, Sahar, et al. AI-Based Assistance System for Manufacturing. 2022,
doi:10.1109/ETFA52439.2022.9921520.
short: S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke,
(2022).
conference:
end_date: 2022-09-09
location: Stuttgart
name: ETFA
start_date: 2022-09-06
date_created: 2022-10-28T11:43:49Z
date_updated: 2023-11-23T08:07:51Z
department:
- _id: '178'
- _id: '574'
- _id: '184'
doi: 10.1109/ETFA52439.2022.9921520
keyword:
- Assistance system
- Knowledge graph
- Information retrieval
- Neural networks
- AR
language:
- iso: eng
project:
- _id: '409'
grant_number: 02L19C115
name: 'KIAM: KIAM: Kompetenzzentrum KI in der Arbeitswelt des industriellen Mittelstands
in OstWestfalenLippe'
related_material:
link:
- relation: confirmation
url: https://ieeexplore.ieee.org/document/9921520
series_title: 2022 IEEE 27th International Conference on Emerging Technologies and
Factory Automation (ETFA)
status: public
title: AI-Based Assistance System for Manufacturing
type: conference
user_id: '44648'
year: '2022'
...
---
_id: '46306'
abstract:
- lang: eng
text: Hyperparameter optimization (HPO) is a key component of machine learning models
for achieving peak predictive performance. While numerous methods and algorithms
for HPO have been proposed over the last years, little progress has been made
in illuminating and examining the actual structure of these black-box optimization
problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that
can be used to gain knowledge about properties of unknown optimization problems.
In this paper, we evaluate the performance of five different black-box optimizers
on 30 HPO problems, which consist of two-, three- and five-dimensional continuous
search spaces of the XGBoost learner trained on 10 different data sets. This is
contrasted with the performance of the same optimizers evaluated on 360 problem
instances from the black-box optimization benchmark (BBOB). We then compute ELA
features on the HPO and BBOB problems and examine similarities and differences.
A cluster analysis of the HPO and BBOB problems in ELA feature space allows us
to identify how the HPO problems compare to the BBOB problems on a structural
meta-level. We identify a subset of BBOB problems that are close to the HPO problems
in ELA feature space and show that optimizer performance is comparably similar
on these two sets of benchmark problems. We highlight open challenges of ELA for
HPO and discuss potential directions of future research and applications.
author:
- first_name: Lennart
full_name: Schneider, Lennart
last_name: Schneider
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Bernd
full_name: Bischl, Bernd
last_name: Bischl
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
citation:
ama: 'Schneider L, Schäpermeier L, Prager RP, Bischl B, Trautmann H, Kerschke P.
HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory
Landscape Analysis. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G,
Tušar T, eds. Parallel Problem Solving from Nature — PPSN XVII. Springer
International Publishing; 2022:575–589. doi:10.1007/978-3-031-14714-2_40'
apa: 'Schneider, L., Schäpermeier, L., Prager, R. P., Bischl, B., Trautmann, H.,
& Kerschke, P. (2022). HPO x ELA: Investigating Hyperparameter Optimization
Landscapes by Means of Exploratory Landscape Analysis. In G. Rudolph, A. V. Kononova,
H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem
Solving from Nature — PPSN XVII (pp. 575–589). Springer International Publishing.
https://doi.org/10.1007/978-3-031-14714-2_40'
bibtex: '@inproceedings{Schneider_Schäpermeier_Prager_Bischl_Trautmann_Kerschke_2022,
place={Cham}, title={HPO x ELA: Investigating Hyperparameter Optimization Landscapes
by Means of Exploratory Landscape Analysis}, DOI={10.1007/978-3-031-14714-2_40},
booktitle={Parallel Problem Solving from Nature — PPSN XVII}, publisher={Springer
International Publishing}, author={Schneider, Lennart and Schäpermeier, Lennart
and Prager, Raphael Patrick and Bischl, Bernd and Trautmann, Heike and Kerschke,
Pascal}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and
Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}, year={2022}, pages={575–589}
}'
chicago: 'Schneider, Lennart, Lennart Schäpermeier, Raphael Patrick Prager, Bernd
Bischl, Heike Trautmann, and Pascal Kerschke. “HPO x ELA: Investigating Hyperparameter
Optimization Landscapes by Means of Exploratory Landscape Analysis.” In Parallel
Problem Solving from Nature — PPSN XVII, edited by Günter Rudolph, Anna V.
Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tušar, 575–589.
Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_40.'
ieee: 'L. Schneider, L. Schäpermeier, R. P. Prager, B. Bischl, H. Trautmann, and
P. Kerschke, “HPO x ELA: Investigating Hyperparameter Optimization Landscapes
by Means of Exploratory Landscape Analysis,” in Parallel Problem Solving from
Nature — PPSN XVII, 2022, pp. 575–589, doi: 10.1007/978-3-031-14714-2_40.'
mla: 'Schneider, Lennart, et al. “HPO x ELA: Investigating Hyperparameter Optimization
Landscapes by Means of Exploratory Landscape Analysis.” Parallel Problem Solving
from Nature — PPSN XVII, edited by Günter Rudolph et al., Springer International
Publishing, 2022, pp. 575–589, doi:10.1007/978-3-031-14714-2_40.'
short: 'L. Schneider, L. Schäpermeier, R.P. Prager, B. Bischl, H. Trautmann, P.
Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T.
Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International
Publishing, Cham, 2022, pp. 575–589.'
date_created: 2023-08-04T07:15:16Z
date_updated: 2023-10-16T12:51:27Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-031-14714-2_40
editor:
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Hernán
full_name: Aguirre, Hernán
last_name: Aguirre
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Gabriela
full_name: Ochoa, Gabriela
last_name: Ochoa
- first_name: Tea
full_name: Tušar, Tea
last_name: Tušar
language:
- iso: eng
page: 575–589
place: Cham
publication: Parallel Problem Solving from Nature — PPSN XVII
publication_identifier:
isbn:
- 978-3-031-14714-2
publisher: Springer International Publishing
status: public
title: 'HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of
Exploratory Landscape Analysis'
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '46308'
abstract:
- lang: eng
text: Single-objective continuous optimization can be challenging, especially when
dealing with multimodal problems. This work sheds light on the effects that multi-objective
optimization may have in the single-objective space. For this purpose, we examine
the inner mechanisms of the recently developed sophisticated local search procedure
SOMOGSA. This method solves multimodal single-objective continuous optimization
problems based on first expanding the problem with an additional objective (e.g.,
a sphere function) to the bi-objective domain and subsequently exploiting local
structures of the resulting landscapes. Our study particularly focuses on the
sensitivity of this multiobjectivization approach w.r.t. (1) the parametrization
of the artificial second objective, as well as (2) the position of the initial
starting points in the search space. As SOMOGSA is a modular framework for encapsulating
local search, we integrate Nelder–Mead local search as optimizer in the respective
module and compare the performance of the resulting hybrid local search to its
original single-objective counterpart. We show that the SOMOGSA framework can
significantly boost local search by multiobjectivization. Hence, combined with
more sophisticated local search and metaheuristics, this may help solve highly
multimodal optimization problems in the future.
author:
- first_name: Pelin
full_name: Aspar, Pelin
last_name: Aspar
- first_name: Vera
full_name: Steinhoff, Vera
last_name: Steinhoff
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
citation:
ama: 'Aspar P, Steinhoff V, Schäpermeier L, Kerschke P, Trautmann H, Grimme C. The
objective that freed me: a multi-objective local search approach for continuous
single-objective optimization. Natural Computing. 2022;1:1–15. doi:10.1007/s11047-022-09919-w'
apa: 'Aspar, P., Steinhoff, V., Schäpermeier, L., Kerschke, P., Trautmann, H., &
Grimme, C. (2022). The objective that freed me: a multi-objective local search
approach for continuous single-objective optimization. Natural Computing,
1, 1–15. https://doi.org/10.1007/s11047-022-09919-w'
bibtex: '@article{Aspar_Steinhoff_Schäpermeier_Kerschke_Trautmann_Grimme_2022, title={The
objective that freed me: a multi-objective local search approach for continuous
single-objective optimization}, volume={1}, DOI={10.1007/s11047-022-09919-w},
journal={Natural Computing}, author={Aspar, Pelin and Steinhoff, Vera and Schäpermeier,
Lennart and Kerschke, Pascal and Trautmann, Heike and Grimme, Christian}, year={2022},
pages={1–15} }'
chicago: 'Aspar, Pelin, Vera Steinhoff, Lennart Schäpermeier, Pascal Kerschke, Heike
Trautmann, and Christian Grimme. “The Objective That Freed Me: A Multi-Objective
Local Search Approach for Continuous Single-Objective Optimization.” Natural
Computing 1 (2022): 1–15. https://doi.org/10.1007/s11047-022-09919-w.'
ieee: 'P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, and C.
Grimme, “The objective that freed me: a multi-objective local search approach
for continuous single-objective optimization,” Natural Computing, vol.
1, pp. 1–15, 2022, doi: 10.1007/s11047-022-09919-w.'
mla: 'Aspar, Pelin, et al. “The Objective That Freed Me: A Multi-Objective Local
Search Approach for Continuous Single-Objective Optimization.” Natural Computing,
vol. 1, 2022, pp. 1–15, doi:10.1007/s11047-022-09919-w.'
short: P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, C. Grimme,
Natural Computing 1 (2022) 1–15.
date_created: 2023-08-04T07:16:40Z
date_updated: 2023-10-16T12:52:33Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/s11047-022-09919-w
intvolume: ' 1'
language:
- iso: eng
page: 1–15
publication: Natural Computing
status: public
title: 'The objective that freed me: a multi-objective local search approach for continuous
single-objective optimization'
type: journal_article
user_id: '15504'
volume: 1
year: '2022'
...
---
_id: '48299'
abstract:
- lang: eng
text: Graph convolutional networks (GCNs) are a powerful architecture for representation
learning on documents that naturally occur as graphs, e.g., citation or social
networks. However, sensitive personal information, such as documents with people{’}s
profiles or relationships as edges, are prone to privacy leaks, as the trained
model might reveal the original input. Although differential privacy (DP) offers
a well-founded privacy-preserving framework, GCNs pose theoretical and practical
challenges due to their training specifics. We address these challenges by adapting
differentially-private gradient-based training to GCNs and conduct experiments
using two optimizers on five NLP datasets in two languages. We propose a simple
yet efficient method based on random graph splits that not only improves the baseline
privacy bounds by a factor of 2.7 while retaining competitive F1 scores, but also
provides strong privacy guarantees of epsilon = 1.0. We show that, under certain
modeling choices, privacy-preserving GCNs perform up to 90{%} of their non-private
variants, while formally guaranteeing strong privacy measures.
author:
- first_name: Timour
full_name: Igamberdiev, Timour
last_name: Igamberdiev
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
citation:
ama: 'Igamberdiev T, Habernal I. Privacy-Preserving Graph Convolutional Networks
for Text Classification. In: Proceedings of the Thirteenth Language Resources
and Evaluation Conference. European Language Resources Association; 2022:338–350.'
apa: Igamberdiev, T., & Habernal, I. (2022). Privacy-Preserving Graph Convolutional
Networks for Text Classification. Proceedings of the Thirteenth Language Resources
and Evaluation Conference, 338–350.
bibtex: '@inproceedings{Igamberdiev_Habernal_2022, place={Marseille, France}, title={Privacy-Preserving
Graph Convolutional Networks for Text Classification}, booktitle={Proceedings
of the Thirteenth Language Resources and Evaluation Conference}, publisher={European
Language Resources Association}, author={Igamberdiev, Timour and Habernal, Ivan},
year={2022}, pages={338–350} }'
chicago: 'Igamberdiev, Timour, and Ivan Habernal. “Privacy-Preserving Graph Convolutional
Networks for Text Classification.” In Proceedings of the Thirteenth Language
Resources and Evaluation Conference, 338–350. Marseille, France: European
Language Resources Association, 2022.'
ieee: T. Igamberdiev and I. Habernal, “Privacy-Preserving Graph Convolutional Networks
for Text Classification,” in Proceedings of the Thirteenth Language Resources
and Evaluation Conference, 2022, pp. 338–350.
mla: Igamberdiev, Timour, and Ivan Habernal. “Privacy-Preserving Graph Convolutional
Networks for Text Classification.” Proceedings of the Thirteenth Language Resources
and Evaluation Conference, European Language Resources Association, 2022,
pp. 338–350.
short: 'T. Igamberdiev, I. Habernal, in: Proceedings of the Thirteenth Language
Resources and Evaluation Conference, European Language Resources Association,
Marseille, France, 2022, pp. 338–350.'
date_created: 2023-10-19T08:26:58Z
date_updated: 2023-10-19T12:05:12Z
department:
- _id: '34'
- _id: '820'
language:
- iso: eng
page: 338–350
place: Marseille, France
publication: Proceedings of the Thirteenth Language Resources and Evaluation Conference
publisher: European Language Resources Association
status: public
title: Privacy-Preserving Graph Convolutional Networks for Text Classification
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '48300'
abstract:
- lang: eng
text: Text rewriting with differential privacy (DP) provides concrete theoretical
guarantees for protecting the privacy of individuals in textual documents. In
practice, existing systems may lack the means to validate their privacy-preserving
claims, leading to problems of transparency and reproducibility. We introduce
DP-Rewrite, an open-source framework for differentially private text rewriting
which aims to solve these problems by being modular, extensible, and highly customizable.
Our system incorporates a variety of downstream datasets, models, pre-training
procedures, and evaluation metrics to provide a flexible way to lead and validate
private text rewriting research. To demonstrate our software in practice, we provide
a set of experiments as a case study on the ADePT DP text rewriting system, detecting
a privacy leak in its pre-training approach. Our system is publicly available,
and we hope that it will help the community to make DP text rewriting research
more accessible and transparent.
author:
- first_name: Timour
full_name: Igamberdiev, Timour
last_name: Igamberdiev
- first_name: Thomas
full_name: Arnold, Thomas
last_name: Arnold
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
citation:
ama: 'Igamberdiev T, Arnold T, Habernal I. DP-Rewrite: Towards Reproducibility and
Transparency in Differentially Private Text Rewriting. In: Proceedings of the
29th International Conference on Computational Linguistics. International
Committee on Computational Linguistics; 2022:2927–2933.'
apa: 'Igamberdiev, T., Arnold, T., & Habernal, I. (2022). DP-Rewrite: Towards
Reproducibility and Transparency in Differentially Private Text Rewriting. Proceedings
of the 29th International Conference on Computational Linguistics, 2927–2933.'
bibtex: '@inproceedings{Igamberdiev_Arnold_Habernal_2022, place={Gyeongju, Republic
of Korea}, title={DP-Rewrite: Towards Reproducibility and Transparency in Differentially
Private Text Rewriting}, booktitle={Proceedings of the 29th International Conference
on Computational Linguistics}, publisher={International Committee on Computational
Linguistics}, author={Igamberdiev, Timour and Arnold, Thomas and Habernal, Ivan},
year={2022}, pages={2927–2933} }'
chicago: 'Igamberdiev, Timour, Thomas Arnold, and Ivan Habernal. “DP-Rewrite: Towards
Reproducibility and Transparency in Differentially Private Text Rewriting.” In
Proceedings of the 29th International Conference on Computational Linguistics,
2927–2933. Gyeongju, Republic of Korea: International Committee on Computational
Linguistics, 2022.'
ieee: 'T. Igamberdiev, T. Arnold, and I. Habernal, “DP-Rewrite: Towards Reproducibility
and Transparency in Differentially Private Text Rewriting,” in Proceedings
of the 29th International Conference on Computational Linguistics, 2022, pp.
2927–2933.'
mla: 'Igamberdiev, Timour, et al. “DP-Rewrite: Towards Reproducibility and Transparency
in Differentially Private Text Rewriting.” Proceedings of the 29th International
Conference on Computational Linguistics, International Committee on Computational
Linguistics, 2022, pp. 2927–2933.'
short: 'T. Igamberdiev, T. Arnold, I. Habernal, in: Proceedings of the 29th International
Conference on Computational Linguistics, International Committee on Computational
Linguistics, Gyeongju, Republic of Korea, 2022, pp. 2927–2933.'
date_created: 2023-10-19T08:27:05Z
date_updated: 2023-10-19T12:04:57Z
department:
- _id: '34'
- _id: '820'
language:
- iso: eng
page: 2927–2933
place: Gyeongju, Republic of Korea
publication: Proceedings of the 29th International Conference on Computational Linguistics
publisher: International Committee on Computational Linguistics
status: public
title: 'DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private
Text Rewriting'
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '48298'
author:
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
citation:
ama: 'Habernal I. How reparametrization trick broke differentially-private text
representation learning. In: Proceedings of the 60th Annual Meeting of the
Association for Computational Linguistics (Volume 2: Short Papers). Association
for Computational Linguistics; 2022. doi:10.18653/v1/2022.acl-short.87'
apa: 'Habernal, I. (2022). How reparametrization trick broke differentially-private
text representation learning. Proceedings of the 60th Annual Meeting of the
Association for Computational Linguistics (Volume 2: Short Papers). https://doi.org/10.18653/v1/2022.acl-short.87'
bibtex: '@inproceedings{Habernal_2022, title={How reparametrization trick broke
differentially-private text representation learning}, DOI={10.18653/v1/2022.acl-short.87},
booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics (Volume 2: Short Papers)}, publisher={Association for Computational
Linguistics}, author={Habernal, Ivan}, year={2022} }'
chicago: 'Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private
Text Representation Learning.” In Proceedings of the 60th Annual Meeting of
the Association for Computational Linguistics (Volume 2: Short Papers). Association
for Computational Linguistics, 2022. https://doi.org/10.18653/v1/2022.acl-short.87.'
ieee: 'I. Habernal, “How reparametrization trick broke differentially-private text
representation learning,” 2022, doi: 10.18653/v1/2022.acl-short.87.'
mla: 'Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private
Text Representation Learning.” Proceedings of the 60th Annual Meeting of the
Association for Computational Linguistics (Volume 2: Short Papers), Association
for Computational Linguistics, 2022, doi:10.18653/v1/2022.acl-short.87.'
short: 'I. Habernal, in: Proceedings of the 60th Annual Meeting of the Association
for Computational Linguistics (Volume 2: Short Papers), Association for Computational
Linguistics, 2022.'
date_created: 2023-10-19T08:26:35Z
date_updated: 2023-10-19T12:05:39Z
department:
- _id: '34'
- _id: '820'
doi: 10.18653/v1/2022.acl-short.87
language:
- iso: eng
publication: 'Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics (Volume 2: Short Papers)'
publication_status: published
publisher: Association for Computational Linguistics
status: public
title: How reparametrization trick broke differentially-private text representation
learning
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '49350'
author:
- first_name: Jonathan
full_name: Brock, Jonathan
last_name: Brock
- first_name: Sebastian
full_name: von Enzberg, Sebastian
last_name: von Enzberg
- first_name: Arno
full_name: Kühn, Arno
last_name: Kühn
- first_name: Roman
full_name: Dumitrescu, Roman
id: '16190'
last_name: Dumitrescu
citation:
ama: 'Brock J, von Enzberg S, Kühn A, Dumitrescu R. Nutzung von Process Mining in
RPA-Projekten. In: Praxishandbuch Robotic Process Automation (RPA). Springer
Fachmedien Wiesbaden; 2022. doi:10.1007/978-3-658-38379-4_5'
apa: Brock, J., von Enzberg, S., Kühn, A., & Dumitrescu, R. (2022). Nutzung
von Process Mining in RPA-Projekten. In Praxishandbuch Robotic Process Automation
(RPA). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-38379-4_5
bibtex: '@inbook{Brock_von Enzberg_Kühn_Dumitrescu_2022, place={Wiesbaden}, title={Nutzung
von Process Mining in RPA-Projekten}, DOI={10.1007/978-3-658-38379-4_5},
booktitle={Praxishandbuch Robotic Process Automation (RPA)}, publisher={Springer
Fachmedien Wiesbaden}, author={Brock, Jonathan and von Enzberg, Sebastian and
Kühn, Arno and Dumitrescu, Roman}, year={2022} }'
chicago: 'Brock, Jonathan, Sebastian von Enzberg, Arno Kühn, and Roman Dumitrescu.
“Nutzung von Process Mining in RPA-Projekten.” In Praxishandbuch Robotic Process
Automation (RPA). Wiesbaden: Springer Fachmedien Wiesbaden, 2022. https://doi.org/10.1007/978-3-658-38379-4_5.'
ieee: 'J. Brock, S. von Enzberg, A. Kühn, and R. Dumitrescu, “Nutzung von Process
Mining in RPA-Projekten,” in Praxishandbuch Robotic Process Automation (RPA),
Wiesbaden: Springer Fachmedien Wiesbaden, 2022.'
mla: Brock, Jonathan, et al. “Nutzung von Process Mining in RPA-Projekten.” Praxishandbuch
Robotic Process Automation (RPA), Springer Fachmedien Wiesbaden, 2022, doi:10.1007/978-3-658-38379-4_5.
short: 'J. Brock, S. von Enzberg, A. Kühn, R. Dumitrescu, in: Praxishandbuch Robotic
Process Automation (RPA), Springer Fachmedien Wiesbaden, Wiesbaden, 2022.'
date_created: 2023-11-30T08:25:53Z
date_updated: 2023-11-30T08:27:28Z
department:
- _id: '563'
doi: 10.1007/978-3-658-38379-4_5
language:
- iso: eng
place: Wiesbaden
publication: Praxishandbuch Robotic Process Automation (RPA)
publication_identifier:
isbn:
- '9783658383787'
- '9783658383794'
publication_status: published
publisher: Springer Fachmedien Wiesbaden
status: public
title: Nutzung von Process Mining in RPA-Projekten
type: book_chapter
user_id: '15782'
year: '2022'
...
---
_id: '33983'
author:
- first_name: Michel
full_name: Scholtysik, Michel
id: '50562'
last_name: Scholtysik
- first_name: Malte
full_name: Rohde, Malte
last_name: Rohde
- first_name: Christian
full_name: Koldewey, Christian
id: '43136'
last_name: Koldewey
orcid: https://orcid.org/0000-0001-7992-6399
- first_name: Roman
full_name: Dumitrescu, Roman
id: '16190'
last_name: Dumitrescu
citation:
ama: 'Scholtysik M, Rohde M, Koldewey C, Dumitrescu R. Adapting the product design
to the circular economy using R-principles. In: ; 2022.'
apa: Scholtysik, M., Rohde, M., Koldewey, C., & Dumitrescu, R. (2022). Adapting
the product design to the circular economy using R-principles.
bibtex: '@inproceedings{Scholtysik_Rohde_Koldewey_Dumitrescu_2022, title={Adapting
the product design to the circular economy using R-principles}, author={Scholtysik,
Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}, year={2022}
}'
chicago: Scholtysik, Michel, Malte Rohde, Christian Koldewey, and Roman Dumitrescu.
“Adapting the Product Design to the Circular Economy Using R-Principles,” 2022.
ieee: M. Scholtysik, M. Rohde, C. Koldewey, and R. Dumitrescu, “Adapting the product
design to the circular economy using R-principles,” 2022.
mla: Scholtysik, Michel, et al. Adapting the Product Design to the Circular Economy
Using R-Principles. 2022.
short: 'M. Scholtysik, M. Rohde, C. Koldewey, R. Dumitrescu, in: 2022.'
date_created: 2022-11-03T07:09:51Z
date_updated: 2023-11-30T10:51:01Z
ddc:
- '620'
department:
- _id: '563'
file:
- access_level: closed
content_type: application/pdf
creator: mscholt2
date_created: 2022-11-03T07:08:50Z
date_updated: 2022-11-03T07:08:50Z
file_id: '33984'
file_name: '[SRK+22] Adapting the product design to the circular economy using R-Principles.pdf'
file_size: 783187
relation: main_file
success: 1
file_date_updated: 2022-11-03T07:08:50Z
has_accepted_license: '1'
language:
- iso: eng
status: public
title: Adapting the product design to the circular economy using R-principles
type: conference
user_id: '50562'
year: '2022'
...
---
_id: '30883'
author:
- first_name: Sarah Claudia
full_name: Krings, Sarah Claudia
id: '64063'
last_name: Krings
orcid: 0000-0001-8040-7553
- first_name: Enes
full_name: Yigitbas, Enes
id: '8447'
last_name: Yigitbas
orcid: 0000-0002-5967-833X
- first_name: Kai
full_name: Biermeier, Kai
id: '55908'
last_name: Biermeier
orcid: 0000-0002-2879-2359
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Krings SC, Yigitbas E, Biermeier K, Engels G. Design and Evaluation of AR-Assisted
End-User Robot Path Planning Strategies. In: Proceedings of the 14th ACM SIGCHI
Symposium on Engineering Interactive Computing Systems (EICS 2022). ; 2022.'
apa: Krings, S. C., Yigitbas, E., Biermeier, K., & Engels, G. (2022). Design
and Evaluation of AR-Assisted End-User Robot Path Planning Strategies. Proceedings
of the 14th ACM SIGCHI Symposium on Engineering Interactive Computing Systems
(EICS 2022).
bibtex: '@inproceedings{Krings_Yigitbas_Biermeier_Engels_2022, title={Design and
Evaluation of AR-Assisted End-User Robot Path Planning Strategies}, booktitle={Proceedings
of the 14th ACM SIGCHI Symposium on Engineering Interactive Computing Systems
(EICS 2022)}, author={Krings, Sarah Claudia and Yigitbas, Enes and Biermeier,
Kai and Engels, Gregor}, year={2022} }'
chicago: Krings, Sarah Claudia, Enes Yigitbas, Kai Biermeier, and Gregor Engels.
“Design and Evaluation of AR-Assisted End-User Robot Path Planning Strategies.”
In Proceedings of the 14th ACM SIGCHI Symposium on Engineering Interactive
Computing Systems (EICS 2022), 2022.
ieee: S. C. Krings, E. Yigitbas, K. Biermeier, and G. Engels, “Design and Evaluation
of AR-Assisted End-User Robot Path Planning Strategies,” 2022.
mla: Krings, Sarah Claudia, et al. “Design and Evaluation of AR-Assisted End-User
Robot Path Planning Strategies.” Proceedings of the 14th ACM SIGCHI Symposium
on Engineering Interactive Computing Systems (EICS 2022), 2022.
short: 'S.C. Krings, E. Yigitbas, K. Biermeier, G. Engels, in: Proceedings of the
14th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2022),
2022.'
date_created: 2022-04-13T08:11:15Z
date_updated: 2023-12-07T10:42:07Z
department:
- _id: '66'
- _id: '534'
language:
- iso: eng
publication: Proceedings of the 14th ACM SIGCHI Symposium on Engineering Interactive
Computing Systems (EICS 2022)
status: public
title: Design and Evaluation of AR-Assisted End-User Robot Path Planning Strategies
type: conference
user_id: '8447'
year: '2022'
...
---
_id: '48861'
abstract:
- lang: eng
text: Generating instances of different properties is key to algorithm selection
methods that differentiate between the performance of different solvers for a
given combinatorial optimization problem. A wide range of methods using evolutionary
computation techniques has been introduced in recent years. With this paper, we
contribute to this area of research by providing a new approach based on quality
diversity (QD) that is able to explore the whole feature space. QD algorithms
allow to create solutions of high quality within a given feature space by splitting
it up into boxes and improving solution quality within each box. We use our QD
approach for the generation of TSP instances to visualize and analyze the variety
of instances differentiating various TSP solvers and compare it to instances generated
by established approaches from the literature.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Bossek J, Neumann F. Exploring the Feature Space of TSP Instances Using Quality
Diversity. In: Proceedings of the Genetic and Evolutionary Computation Conference.
GECCO ’22. Association for Computing Machinery; 2022:186–194. doi:10.1145/3512290.3528851'
apa: Bossek, J., & Neumann, F. (2022). Exploring the Feature Space of TSP Instances
Using Quality Diversity. Proceedings of the Genetic and Evolutionary Computation
Conference, 186–194. https://doi.org/10.1145/3512290.3528851
bibtex: '@inproceedings{Bossek_Neumann_2022, place={New York, NY, USA}, series={GECCO
’22}, title={Exploring the Feature Space of TSP Instances Using Quality Diversity},
DOI={10.1145/3512290.3528851},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann,
Frank}, year={2022}, pages={186–194}, collection={GECCO ’22} }'
chicago: 'Bossek, Jakob, and Frank Neumann. “Exploring the Feature Space of TSP
Instances Using Quality Diversity.” In Proceedings of the Genetic and Evolutionary
Computation Conference, 186–194. GECCO ’22. New York, NY, USA: Association
for Computing Machinery, 2022. https://doi.org/10.1145/3512290.3528851.'
ieee: 'J. Bossek and F. Neumann, “Exploring the Feature Space of TSP Instances Using
Quality Diversity,” in Proceedings of the Genetic and Evolutionary Computation
Conference, 2022, pp. 186–194, doi: 10.1145/3512290.3528851.'
mla: Bossek, Jakob, and Frank Neumann. “Exploring the Feature Space of TSP Instances
Using Quality Diversity.” Proceedings of the Genetic and Evolutionary Computation
Conference, Association for Computing Machinery, 2022, pp. 186–194, doi:10.1145/3512290.3528851.
short: 'J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation
Conference, Association for Computing Machinery, New York, NY, USA, 2022, pp.
186–194.'
date_created: 2023-11-14T15:58:55Z
date_updated: 2023-12-13T10:45:56Z
department:
- _id: '819'
doi: 10.1145/3512290.3528851
extern: '1'
keyword:
- instance features
- instance generation
- quality diversity
- TSP
language:
- iso: eng
page: 186–194
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-9237-2
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’22
status: public
title: Exploring the Feature Space of TSP Instances Using Quality Diversity
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48868'
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Aneta
full_name: Neumann, Aneta
last_name: Neumann
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Bossek J, Neumann A, Neumann F. Evolutionary Diversity Optimization for Combinatorial
Optimization: Tutorial at GECCO’22, Boston, USA. In: Proceedings of the Genetic
and Evolutionary Computation Conference Companion. GECCO’22. Association for
Computing Machinery; 2022:824–842. doi:10.1145/3520304.3533626'
apa: 'Bossek, J., Neumann, A., & Neumann, F. (2022). Evolutionary Diversity
Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA.
Proceedings of the Genetic and Evolutionary Computation Conference Companion,
824–842. https://doi.org/10.1145/3520304.3533626'
bibtex: '@inproceedings{Bossek_Neumann_Neumann_2022, place={New York, NY, USA},
series={GECCO’22}, title={Evolutionary Diversity Optimization for Combinatorial
Optimization: Tutorial at GECCO’22, Boston, USA}, DOI={10.1145/3520304.3533626},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
Companion}, publisher={Association for Computing Machinery}, author={Bossek, Jakob
and Neumann, Aneta and Neumann, Frank}, year={2022}, pages={824–842}, collection={GECCO’22}
}'
chicago: 'Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Evolutionary Diversity
Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA.”
In Proceedings of the Genetic and Evolutionary Computation Conference Companion,
824–842. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022.
https://doi.org/10.1145/3520304.3533626.'
ieee: 'J. Bossek, A. Neumann, and F. Neumann, “Evolutionary Diversity Optimization
for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA,” in Proceedings
of the Genetic and Evolutionary Computation Conference Companion, 2022, pp.
824–842, doi: 10.1145/3520304.3533626.'
mla: 'Bossek, Jakob, et al. “Evolutionary Diversity Optimization for Combinatorial
Optimization: Tutorial at GECCO’22, Boston, USA.” Proceedings of the Genetic
and Evolutionary Computation Conference Companion, Association for Computing
Machinery, 2022, pp. 824–842, doi:10.1145/3520304.3533626.'
short: 'J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary
Computation Conference Companion, Association for Computing Machinery, New York,
NY, USA, 2022, pp. 824–842.'
date_created: 2023-11-14T15:58:56Z
date_updated: 2023-12-13T10:46:19Z
department:
- _id: '819'
doi: 10.1145/3520304.3533626
extern: '1'
language:
- iso: eng
page: 824–842
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference Companion
publication_identifier:
isbn:
- 978-1-4503-9268-6
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO’22
status: public
title: 'Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial
at GECCO’22, Boston, USA'
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48882'
abstract:
- lang: eng
text: In multimodal multi-objective optimization (MMMOO), the focus is not solely
on convergence in objective space, but rather also on explicitly ensuring diversity
in decision space. We illustrate why commonly used diversity measures are not
entirely appropriate for this task and propose a sophisticated basin-based evaluation
(BBE) method. Also, BBE variants are developed, capturing the anytime behavior
of algorithms. The set of BBE measures is tested by means of an algorithm configuration
study. We show that these new measures also transfer properties of the well-established
hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective
space convergence. Moreover, we advance MMMOO research by providing insights into
the multimodal performance of the considered algorithms. Specifically, algorithms
exploiting local structures are shown to outperform classical evolutionary multi-objective
optimizers regarding the BBE variants and respective trade-off with HV.
author:
- first_name: Jonathan
full_name: Heins, Jonathan
last_name: Heins
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based
Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G,
Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. Parallel Problem
Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer
International Publishing; 2022:192–206. doi:10.1007/978-3-031-14714-2_14'
apa: 'Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., & Trautmann,
H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization
Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &
T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp.
192–206). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_14'
bibtex: '@inproceedings{Heins_Rook_Schäpermeier_Kerschke_Bossek_Trautmann_2022,
place={Cham}, series={Lecture Notes in Computer Science}, title={BBE: Basin-Based
Evaluation of Multimodal Multi-objective Optimization Problems}, DOI={10.1007/978-3-031-14714-2_14},
booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer
International Publishing}, author={Heins, Jonathan and Rook, Jeroen and Schäpermeier,
Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}, editor={Rudolph,
Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa,
Gabriela and Tusar, Tea}, year={2022}, pages={192–206}, collection={Lecture Notes
in Computer Science} }'
chicago: 'Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob
Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective
Optimization Problems.” In Parallel Problem Solving from Nature (PPSN XVII),
edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela
Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer
International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_14.'
ieee: 'J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann,
“BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,”
in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 192–206,
doi: 10.1007/978-3-031-14714-2_14.'
mla: 'Heins, Jonathan, et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective
Optimization Problems.” Parallel Problem Solving from Nature (PPSN XVII),
edited by Günter Rudolph et al., Springer International Publishing, 2022, pp.
192–206, doi:10.1007/978-3-031-14714-2_14.'
short: 'J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann,
in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.),
Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing,
Cham, 2022, pp. 192–206.'
date_created: 2023-11-14T15:58:58Z
date_updated: 2023-12-13T10:47:50Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_14
editor:
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Hernán
full_name: Aguirre, Hernán
last_name: Aguirre
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Gabriela
full_name: Ochoa, Gabriela
last_name: Ochoa
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
extern: '1'
keyword:
- Anytime behavior
- Benchmarking
- Continuous optimization
- Multi-objective optimization
- Multimodality
- Performance metric
language:
- iso: eng
page: 192–206
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
isbn:
- 978-3-031-14714-2
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: 'BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems'
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48894'
abstract:
- lang: eng
text: Recently different evolutionary computation approaches have been developed
that generate sets of high quality diverse solutions for a given optimisation
problem. Many studies have considered diversity 1) as a mean to explore niches
in behavioural space (quality diversity) or 2) to increase the structural differences
of solutions (evolutionary diversity optimisation). In this study, we introduce
a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component
traveling thief problem. The results show the capability of the co-evolutionary
algorithm to achieve significantly higher diversity compared to the baseline evolutionary
diversity algorithms from the literature.
author:
- first_name: Adel
full_name: Nikfarjam, Adel
last_name: Nikfarjam
- first_name: Aneta
full_name: Neumann, Aneta
last_name: Neumann
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Nikfarjam A, Neumann A, Bossek J, Neumann F. Co-Evolutionary Diversity Optimisation
for the Traveling Thief Problem. In: Rudolph G, Kononova AV, Aguirre H, Kerschke
P, Ochoa G, Tu\v sar T, eds. Parallel Problem Solving from Nature (PPSN XVII).
Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249.
doi:10.1007/978-3-031-14714-2_17'
apa: Nikfarjam, A., Neumann, A., Bossek, J., & Neumann, F. (2022). Co-Evolutionary
Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova,
H. Aguirre, P. Kerschke, G. Ochoa, & T. Tu\v sar (Eds.), Parallel Problem
Solving from Nature (PPSN XVII) (pp. 237–249). Springer International Publishing.
https://doi.org/10.1007/978-3-031-14714-2_17
bibtex: '@inproceedings{Nikfarjam_Neumann_Bossek_Neumann_2022, place={Cham}, series={Lecture
Notes in Computer Science}, title={Co-Evolutionary Diversity Optimisation for
the Traveling Thief Problem}, DOI={10.1007/978-3-031-14714-2_17},
booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer
International Publishing}, author={Nikfarjam, Adel and Neumann, Aneta and Bossek,
Jakob and Neumann, Frank}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre,
Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\v sar, Tea}, year={2022},
pages={237–249}, collection={Lecture Notes in Computer Science} }'
chicago: 'Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary
Diversity Optimisation for the Traveling Thief Problem.” In Parallel Problem
Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova,
Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\v sar, 237–249. Lecture
Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_17.'
ieee: 'A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity
Optimisation for the Traveling Thief Problem,” in Parallel Problem Solving
from Nature (PPSN XVII), 2022, pp. 237–249, doi: 10.1007/978-3-031-14714-2_17.'
mla: Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling
Thief Problem.” Parallel Problem Solving from Nature (PPSN XVII), edited
by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249,
doi:10.1007/978-3-031-14714-2_17.
short: 'A. Nikfarjam, A. Neumann, J. Bossek, F. Neumann, in: G. Rudolph, A.V. Kononova,
H. Aguirre, P. Kerschke, G. Ochoa, T. Tu\v sar (Eds.), Parallel Problem Solving
from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 237–249.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:49:51Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_17
editor:
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Hernán
full_name: Aguirre, Hernán
last_name: Aguirre
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Gabriela
full_name: Ochoa, Gabriela
last_name: Ochoa
- first_name: Tea
full_name: Tu\v sar, Tea
last_name: Tu\v sar
extern: '1'
keyword:
- Co-evolutionary algorithms
- Evolutionary diversity optimisation
- Quality diversity
- Traveling thief problem
language:
- iso: eng
page: 237–249
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
isbn:
- 978-3-031-14714-2
publication_status: published
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
type: conference
user_id: '102979'
year: '2022'
...