---
_id: '5671'
abstract:
- lang: eng
  text: Multi-attribute value theory (MAVT)-based recommender systems have been proposed
    for dealing with issues of existing recommender systems, such as the cold-start
    problem and changing preferences. However, as we argue in this paper, existing
    MAVT-based methods for measuring attribute importance weights do not fit the shopping
    tasks for which recommender systems are typically used. These methods assume well-trained
    decision makers who are willing to invest time and cognitive effort, and who are
    familiar with the attributes describing the available alternatives and the ranges
    of these attribute levels. Yet, recommender systems are most often used by consumers
    who are usually not familiar with the available attributes and ranges and who
    wish to save time and effort. Against this background, we develop a new method,
    based on a product configuration process, which is tailored to the characteristics
    of these particular decision makers. We empirically compare our method to SWING,
    ranking-based conjoint analysis and TRADEOFF in a between-subjects laboratory
    experiment with 153 participants. Results indicate that our proposed method performs
    better than TRADEOFF and CONJOINT and at least as well as SWING in terms of recommendation
    accuracy, better than SWING and TRADEOFF and at least as well as CONJOINT in terms
    of cognitive load, and that participants were faster with our method than with
    any other method. We conclude that our method is a promising option to help support
    consumers' decision processes in e-commerce shopping tasks.
author:
- first_name: Michael
  full_name: Scholz, Michael
  last_name: Scholz
- first_name: Verena
  full_name: Dorner, Verena
  last_name: Dorner
- first_name: Guido
  full_name: Schryen, Guido
  id: '72850'
  last_name: Schryen
- first_name: Alexander
  full_name: Benlian, Alexander
  last_name: Benlian
citation:
  ama: Scholz M, Dorner V, Schryen G, Benlian A. A configuration-based recommender
    system for supporting e-commerce decisions. <i>European Journal of Operational
    Research</i>. 2017;259(1):205-215.
  apa: Scholz, M., Dorner, V., Schryen, G., &#38; Benlian, A. (2017). A configuration-based
    recommender system for supporting e-commerce decisions. <i>European Journal of
    Operational Research</i>, <i>259</i>(1), 205–215.
  bibtex: '@article{Scholz_Dorner_Schryen_Benlian_2017, title={A configuration-based
    recommender system for supporting e-commerce decisions}, volume={259}, number={1},
    journal={European Journal of Operational Research}, publisher={Elsevier}, author={Scholz,
    Michael and Dorner, Verena and Schryen, Guido and Benlian, Alexander}, year={2017},
    pages={205–215} }'
  chicago: 'Scholz, Michael, Verena Dorner, Guido Schryen, and Alexander Benlian.
    “A Configuration-Based Recommender System for Supporting e-Commerce Decisions.”
    <i>European Journal of Operational Research</i> 259, no. 1 (2017): 205–15.'
  ieee: M. Scholz, V. Dorner, G. Schryen, and A. Benlian, “A configuration-based recommender
    system for supporting e-commerce decisions,” <i>European Journal of Operational
    Research</i>, vol. 259, no. 1, pp. 205–215, 2017.
  mla: Scholz, Michael, et al. “A Configuration-Based Recommender System for Supporting
    e-Commerce Decisions.” <i>European Journal of Operational Research</i>, vol. 259,
    no. 1, Elsevier, 2017, pp. 205–15.
  short: M. Scholz, V. Dorner, G. Schryen, A. Benlian, European Journal of Operational
    Research 259 (2017) 205–215.
date_created: 2018-11-14T15:06:18Z
date_updated: 2022-01-06T07:02:27Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
  content_type: application/pdf
  creator: hsiemes
  date_created: 2018-12-07T11:30:59Z
  date_updated: 2018-12-13T15:06:56Z
  file_id: '6025'
  file_name: EJOR article.pdf
  file_size: 762889
  relation: main_file
file_date_updated: 2018-12-13T15:06:56Z
has_accepted_license: '1'
intvolume: '       259'
issue: '1'
keyword:
- E-Commerce
- Recommender System
- Attribute Weights
- Configuration System
- Decision Support
language:
- iso: eng
oa: '1'
page: 205 - 215
publication: European Journal of Operational Research
publisher: Elsevier
status: public
title: A configuration-based recommender system for supporting e-commerce decisions
type: journal_article
user_id: '61579'
volume: 259
year: '2017'
...
---
_id: '680'
author:
- first_name: Manuel
  full_name: Peter, Manuel
  last_name: Peter
- first_name: Andre
  full_name: Hildebrandt, Andre
  last_name: Hildebrandt
- first_name: Christian
  full_name: Schlickriede, Christian
  id: '59792'
  last_name: Schlickriede
- first_name: Kimia
  full_name: Gharib, Kimia
  last_name: Gharib
- first_name: Thomas
  full_name: Zentgraf, Thomas
  id: '30525'
  last_name: Zentgraf
  orcid: 0000-0002-8662-1101
- first_name: Jens
  full_name: Förstner, Jens
  id: '158'
  last_name: Förstner
  orcid: 0000-0001-7059-9862
- first_name: Stefan
  full_name: Linden, Stefan
  last_name: Linden
citation:
  ama: Peter M, Hildebrandt A, Schlickriede C, et al. Directional Emission from Dielectric
    Leaky-Wave Nanoantennas. <i>Nano Letters</i>. 2017;17(7):4178-4183. doi:<a href="https://doi.org/10.1021/acs.nanolett.7b00966">10.1021/acs.nanolett.7b00966</a>
  apa: Peter, M., Hildebrandt, A., Schlickriede, C., Gharib, K., Zentgraf, T., Förstner,
    J., &#38; Linden, S. (2017). Directional Emission from Dielectric Leaky-Wave Nanoantennas.
    <i>Nano Letters</i>, <i>17</i>(7), 4178–4183. <a href="https://doi.org/10.1021/acs.nanolett.7b00966">https://doi.org/10.1021/acs.nanolett.7b00966</a>
  bibtex: '@article{Peter_Hildebrandt_Schlickriede_Gharib_Zentgraf_Förstner_Linden_2017,
    title={Directional Emission from Dielectric Leaky-Wave Nanoantennas}, volume={17},
    DOI={<a href="https://doi.org/10.1021/acs.nanolett.7b00966">10.1021/acs.nanolett.7b00966</a>},
    number={7}, journal={Nano Letters}, publisher={American Chemical Society (ACS)},
    author={Peter, Manuel and Hildebrandt, Andre and Schlickriede, Christian and Gharib,
    Kimia and Zentgraf, Thomas and Förstner, Jens and Linden, Stefan}, year={2017},
    pages={4178–4183} }'
  chicago: 'Peter, Manuel, Andre Hildebrandt, Christian Schlickriede, Kimia Gharib,
    Thomas Zentgraf, Jens Förstner, and Stefan Linden. “Directional Emission from
    Dielectric Leaky-Wave Nanoantennas.” <i>Nano Letters</i> 17, no. 7 (2017): 4178–83.
    <a href="https://doi.org/10.1021/acs.nanolett.7b00966">https://doi.org/10.1021/acs.nanolett.7b00966</a>.'
  ieee: M. Peter <i>et al.</i>, “Directional Emission from Dielectric Leaky-Wave Nanoantennas,”
    <i>Nano Letters</i>, vol. 17, no. 7, pp. 4178–4183, 2017.
  mla: Peter, Manuel, et al. “Directional Emission from Dielectric Leaky-Wave Nanoantennas.”
    <i>Nano Letters</i>, vol. 17, no. 7, American Chemical Society (ACS), 2017, pp.
    4178–83, doi:<a href="https://doi.org/10.1021/acs.nanolett.7b00966">10.1021/acs.nanolett.7b00966</a>.
  short: M. Peter, A. Hildebrandt, C. Schlickriede, K. Gharib, T. Zentgraf, J. Förstner,
    S. Linden, Nano Letters 17 (2017) 4178–4183.
date_created: 2017-11-13T07:36:01Z
date_updated: 2022-01-06T07:03:20Z
ddc:
- '530'
department:
- _id: '61'
- _id: '289'
doi: 10.1021/acs.nanolett.7b00966
file:
- access_level: open_access
  content_type: application/pdf
  creator: fossie
  date_created: 2018-08-16T08:07:31Z
  date_updated: 2018-08-21T10:41:58Z
  file_id: '3917'
  file_name: 2017-08 Peter - Nano Letters - Directional Emission from Dielectric Leaky-Wave
    Antennas.pdf
  file_size: 3398275
  relation: main_file
file_date_updated: 2018-08-21T10:41:58Z
has_accepted_license: '1'
intvolume: '        17'
issue: '7'
keyword:
- tet_topic_opticalantenna
language:
- iso: eng
oa: '1'
page: 4178-4183
project:
- _id: '53'
  name: TRR 142
- _id: '56'
  name: TRR 142 - Project Area C
- _id: '74'
  name: TRR 142 - Subproject C4
publication: Nano Letters
publication_identifier:
  issn:
  - 1530-6984
  - 1530-6992
publication_status: published
publisher: American Chemical Society (ACS)
status: public
title: Directional Emission from Dielectric Leaky-Wave Nanoantennas
type: journal_article
urn: '6808'
user_id: '158'
volume: 17
year: '2017'
...
---
_id: '10594'
abstract:
- lang: eng
  text: "Multiobjective optimization plays an increasingly important role in modern
    applications, where several criteria are often of equal importance. The task in
    multiobjective optimization and multiobjective optimal control is therefore to
    compute\r\nthe set of optimal compromises (the Pareto set) between the conflicting
    objectives.\r\n\r\nSince – in contrast to the solution of a single objective optimization
    problem – the\r\nPareto set generally consists of an infinite number of solutions,
    the computational\r\neffort can quickly become challenging. This is even more
    the case when many problems have to be solved, when the number of objectives is
    high, or when the objectives\r\nare costly to evaluate. Consequently, this thesis
    is devoted to the identification and\r\nexploitation of structure both in the
    Pareto set and the dynamics of the underlying\r\nmodel as well as to the development
    of efficient algorithms for solving problems with\r\nadditional parameters, with
    a high number of objectives or with PDE-constraints.\r\nThese three challenges
    are addressed in three respective parts.\r\n\r\nIn the first part, predictor-corrector
    methods are extended to entire Pareto sets.\r\nWhen certain smoothness assumptions
    are satisfied, then the set of parameter dependent Pareto sets possesses additional
    structure, i.e. it is a manifold. The tangent\r\nspace can be approximated numerically
    which yields a direction for the predictor\r\nstep. In the corrector step, the
    predicted set converges to the Pareto set at a new\r\nparameter value. The resulting
    algorithm is applied to an example from autonomous\r\ndriving.\r\n\r\nIn the second
    part, the hierarchical structure of Pareto sets is investigated. When\r\nconsidering
    a subset of the objectives, the resulting solution is a subset of the Pareto\r\nset
    of the original problem. Under additional smoothness assumptions, the respective
    subsets are located on the boundary of the Pareto set of the full problem. This\r\nway,
    the “skeleton” of a Pareto set can be computed and due to the exponential\r\nincrease
    in computing time with the number of objectives, the computations of\r\nthese
    subsets are significantly faster which is demonstrated using an example from\r\nindustrial
    laundries.\r\n\r\nIn the third part, PDE-constrained multiobjective optimal control
    problems are\r\naddressed by reduced order modeling methods. Reduced order models
    exploit the\r\nstructure in the system dynamics, for example by describing the
    dynamics of only the\r\nmost energetic modes. The model reduction introduces an
    error in both the function values and their gradients, which has to be taken into
    account in the development of\r\nalgorithms. Both scalarization and set-oriented
    approaches are coupled with reduced\r\norder modeling. Convergence results are
    presented and the numerical benefit is\r\ninvestigated. The algorithms are applied
    to semi-linear heat flow problems as well\r\nas to the Navier-Stokes equations.\r\n"
author:
- first_name: Sebastian
  full_name: Peitz, Sebastian
  id: '47427'
  last_name: Peitz
  orcid: https://orcid.org/0000-0002-3389-793X
citation:
  ama: Peitz S. <i>  Exploiting Structure in Multiobjective Optimization and Optimal
    Control</i>.; 2017. doi:<a href="https://doi.org/10.17619/UNIPB/1-176">10.17619/UNIPB/1-176</a>
  apa: Peitz, S. (2017). <i>  Exploiting structure in multiobjective optimization
    and optimal control</i>. <a href="https://doi.org/10.17619/UNIPB/1-176">https://doi.org/10.17619/UNIPB/1-176</a>
  bibtex: '@book{Peitz_2017, title={  Exploiting structure in multiobjective optimization
    and optimal control}, DOI={<a href="https://doi.org/10.17619/UNIPB/1-176">10.17619/UNIPB/1-176</a>},
    author={Peitz, Sebastian}, year={2017} }'
  chicago: Peitz, Sebastian. <i>  Exploiting Structure in Multiobjective Optimization
    and Optimal Control</i>, 2017. <a href="https://doi.org/10.17619/UNIPB/1-176">https://doi.org/10.17619/UNIPB/1-176</a>.
  ieee: S. Peitz, <i>  Exploiting structure in multiobjective optimization and optimal
    control</i>. 2017.
  mla: Peitz, Sebastian. <i>  Exploiting Structure in Multiobjective Optimization
    and Optimal Control</i>. 2017, doi:<a href="https://doi.org/10.17619/UNIPB/1-176">10.17619/UNIPB/1-176</a>.
  short: S. Peitz,   Exploiting Structure in Multiobjective Optimization and Optimal
    Control, 2017.
date_created: 2019-07-10T08:12:22Z
date_updated: 2022-01-06T06:50:46Z
ddc:
- '510'
department:
- _id: '101'
doi: 10.17619/UNIPB/1-176
file:
- access_level: closed
  content_type: application/pdf
  creator: speitz
  date_created: 2020-03-13T12:52:50Z
  date_updated: 2020-03-13T12:52:50Z
  file_id: '16298'
  file_name: Dissertation_Peitz.pdf
  file_size: 16636801
  relation: main_file
  success: 1
file_date_updated: 2020-03-13T12:52:50Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://d-nb.info/1139356542/34
oa: '1'
project:
- _id: '52'
  name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication_status: published
status: public
title: " \tExploiting structure in multiobjective optimization and optimal control"
type: dissertation
user_id: '47427'
year: '2017'
...
---
_id: '1083'
abstract:
- lang: eng
  text: In actual school choice applications the theoretical underpinnings of the
    Boston School Choice Mechanism (BM) (complete information and rationality of the
    agents) are often not given. We analyze the actual behavior of agents in such
    a matching mechanism, using data from the matching mechanism currently used in
    a clearinghouse at a faculty of Business Administration and Economics at a German
    university, where a variant of the BM is used, and supplement this data with data
    generated in a survey among students who participated in the clearinghouse. We
    find that under the current mechanism over 70% of students act strategically.
    Controlling for students' limited information, we find that they do act rationally
    in their decision to act strategically. While students thus seem to react to the
    incentives to act strategically under the BM, they do not seem to be able to use
    this to their own advantage. However, those students acting in line with their
    beliefs manage a significantly better personal outcome than those who do not.
    We also run simulations by using a variant of the deferred acceptance algorithm,
    adapted to our situation, to show that the use of a different algorithm may be
    to the students' advantage.
author:
- first_name: Britta
  full_name: Hoyer, Britta
  id: '42447'
  last_name: Hoyer
- first_name: Nadja
  full_name: Stroh-Maraun, Nadja
  id: '13264'
  last_name: Stroh-Maraun
citation:
  ama: Hoyer B, Stroh-Maraun N. <i>Matching Strategies of Heterogeneous Agents under
    Incomplete Information in a University Clearinghouse</i>. Vol 110. CIE Working
    Paper Series, Paderborn University; 2017.
  apa: Hoyer, B., &#38; Stroh-Maraun, N. (2017). <i>Matching Strategies of Heterogeneous
    Agents under Incomplete Information in a University Clearinghouse</i> (Vol. 110).
    CIE Working Paper Series, Paderborn University.
  bibtex: '@book{Hoyer_Stroh-Maraun_2017, series={Working Papers CIE}, title={Matching
    Strategies of Heterogeneous Agents under Incomplete Information in a University
    Clearinghouse}, volume={110}, publisher={CIE Working Paper Series, Paderborn University},
    author={Hoyer, Britta and Stroh-Maraun, Nadja}, year={2017}, collection={Working
    Papers CIE} }'
  chicago: Hoyer, Britta, and Nadja Stroh-Maraun. <i>Matching Strategies of Heterogeneous
    Agents under Incomplete Information in a University Clearinghouse</i>. Vol. 110.
    Working Papers CIE. CIE Working Paper Series, Paderborn University, 2017.
  ieee: B. Hoyer and N. Stroh-Maraun, <i>Matching Strategies of Heterogeneous Agents
    under Incomplete Information in a University Clearinghouse</i>, vol. 110. CIE
    Working Paper Series, Paderborn University, 2017.
  mla: Hoyer, Britta, and Nadja Stroh-Maraun. <i>Matching Strategies of Heterogeneous
    Agents under Incomplete Information in a University Clearinghouse</i>. Vol. 110,
    CIE Working Paper Series, Paderborn University, 2017.
  short: B. Hoyer, N. Stroh-Maraun, Matching Strategies of Heterogeneous Agents under
    Incomplete Information in a University Clearinghouse, CIE Working Paper Series,
    Paderborn University, 2017.
date_created: 2017-12-20T16:21:51Z
date_updated: 2022-01-06T06:50:51Z
ddc:
- '040'
department:
- _id: '280'
- _id: '205'
- _id: '475'
file:
- access_level: closed
  content_type: application/pdf
  creator: nmaraun
  date_created: 2018-08-15T07:33:12Z
  date_updated: 2018-08-15T07:33:12Z
  file_id: '3911'
  file_name: Matching Strategies of Heterogeneous Agents under Incomplete Information
    in a University Clearinghouse.pdf
  file_size: 346752
  relation: main_file
  success: 1
file_date_updated: 2018-08-15T07:33:12Z
has_accepted_license: '1'
intvolume: '       110'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/ciepap/WP110.pdf
oa: '1'
project:
- _id: '1'
  name: SFB 901
- _id: '2'
  name: SFB 901 - Project Area A
- _id: '7'
  name: SFB 901 - Subproject A3
publisher: CIE Working Paper Series, Paderborn University
series_title: Working Papers CIE
status: public
title: Matching Strategies of Heterogeneous Agents under Incomplete Information in
  a University Clearinghouse
type: working_paper
user_id: '42447'
volume: 110
year: '2017'
...
---
_id: '109'
author:
- first_name: Felix
  full_name: Pauck, Felix
  id: '22398'
  last_name: Pauck
citation:
  ama: Pauck F. <i>Cooperative Static Analysis of Android Applications</i>. Universität
    Paderborn; 2017.
  apa: Pauck, F. (2017). <i>Cooperative static analysis of Android applications</i>.
    Universität Paderborn.
  bibtex: '@book{Pauck_2017, title={Cooperative static analysis of Android applications},
    publisher={Universität Paderborn}, author={Pauck, Felix}, year={2017} }'
  chicago: Pauck, Felix. <i>Cooperative Static Analysis of Android Applications</i>.
    Universität Paderborn, 2017.
  ieee: F. Pauck, <i>Cooperative static analysis of Android applications</i>. Universität
    Paderborn, 2017.
  mla: Pauck, Felix. <i>Cooperative Static Analysis of Android Applications</i>. Universität
    Paderborn, 2017.
  short: F. Pauck, Cooperative Static Analysis of Android Applications, Universität
    Paderborn, 2017.
date_created: 2017-10-17T12:41:12Z
date_updated: 2022-01-06T06:50:52Z
ddc:
- '000'
department:
- _id: '77'
file:
- access_level: open_access
  content_type: application/pdf
  creator: fpauck
  date_created: 2019-08-07T08:55:58Z
  date_updated: 2019-08-07T09:03:48Z
  file_id: '12905'
  file_name: fpauck_2017.pdf
  file_size: 5093611
  relation: main_file
  title: Master's Thesis
file_date_updated: 2019-08-07T09:03:48Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '1'
  name: SFB 901
- _id: '12'
  name: SFB 901 - Subprojekt B4
- _id: '3'
  name: SFB 901 - Project Area B
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Heike
  full_name: Wehrheim, Heike
  id: '573'
  last_name: Wehrheim
title: Cooperative static analysis of Android applications
type: mastersthesis
user_id: '22398'
year: '2017'
...
---
_id: '1095'
abstract:
- lang: eng
  text: 'Many university students struggle with motivational problems, and gamification
    has the potential to address these problems. However, using gamification currently
    is rather tedious and time-consuming for instructors because current approaches
    to gamification require instructors to engage in the time-consuming preparation
    of course contents (e.g., for quizzes or mini-games). In reply to this issue,
    we propose a “lean” approach to gamification, which relies on gamifying learning
    activities rather than learning contents. The learning activities that are gamified
    in the lean approach can typically be drawn from existing course syllabi (e.g.,
    attend certain lectures, hand in assignments, read book chapters and articles).
    Hence, compared to existing approaches, lean gamification substantially lowers
    the time requirements posed on instructors for gamifying a given course. Drawing
    on research on limited attention and the present bias, we provide the theoretical
    foundation for the lean gamification approach. In addition, we present a mobile
    application that implements lean gamification and outline a mixed-methods study
    that is currently under way for evaluating whether lean gamification does indeed
    have the potential to increase students’ motivation. We thereby hope to allow
    more students and instructors to benefit from the advantages of gamification. '
author:
- first_name: Thomas
  full_name: John, Thomas
  id: '3952'
  last_name: John
- first_name: Matthias
  full_name: Feldotto, Matthias
  id: '14052'
  last_name: Feldotto
  orcid: 0000-0003-1348-6516
- first_name: Paul
  full_name: Hemsen, Paul
  id: '22546'
  last_name: Hemsen
- first_name: Katrin
  full_name: Klingsieck, Katrin
  last_name: Klingsieck
- first_name: Dennis
  full_name: Kundisch, Dennis
  id: '21117'
  last_name: Kundisch
- first_name: Mike
  full_name: Langendorf, Mike
  last_name: Langendorf
citation:
  ama: 'John T, Feldotto M, Hemsen P, Klingsieck K, Kundisch D, Langendorf M. Towards
    a Lean Approach for Gamifying Education. In: <i>Proceedings of the 25th European
    Conference on Information Systems (ECIS)</i>. ; 2017:2970-2979.'
  apa: John, T., Feldotto, M., Hemsen, P., Klingsieck, K., Kundisch, D., &#38; Langendorf,
    M. (2017). Towards a Lean Approach for Gamifying Education. In <i>Proceedings
    of the 25th European Conference on Information Systems (ECIS)</i> (pp. 2970–2979).
  bibtex: '@inproceedings{John_Feldotto_Hemsen_Klingsieck_Kundisch_Langendorf_2017,
    title={Towards a Lean Approach for Gamifying Education}, booktitle={Proceedings
    of the 25th European Conference on Information Systems (ECIS)}, author={John,
    Thomas and Feldotto, Matthias and Hemsen, Paul and Klingsieck, Katrin and Kundisch,
    Dennis and Langendorf, Mike}, year={2017}, pages={2970–2979} }'
  chicago: John, Thomas, Matthias Feldotto, Paul Hemsen, Katrin Klingsieck, Dennis
    Kundisch, and Mike Langendorf. “Towards a Lean Approach for Gamifying Education.”
    In <i>Proceedings of the 25th European Conference on Information Systems (ECIS)</i>,
    2970–79, 2017.
  ieee: T. John, M. Feldotto, P. Hemsen, K. Klingsieck, D. Kundisch, and M. Langendorf,
    “Towards a Lean Approach for Gamifying Education,” in <i>Proceedings of the 25th
    European Conference on Information Systems (ECIS)</i>, 2017, pp. 2970–2979.
  mla: John, Thomas, et al. “Towards a Lean Approach for Gamifying Education.” <i>Proceedings
    of the 25th European Conference on Information Systems (ECIS)</i>, 2017, pp. 2970–79.
  short: 'T. John, M. Feldotto, P. Hemsen, K. Klingsieck, D. Kundisch, M. Langendorf,
    in: Proceedings of the 25th European Conference on Information Systems (ECIS),
    2017, pp. 2970–2979.'
date_created: 2018-01-05T08:39:41Z
date_updated: 2022-01-06T06:50:53Z
ddc:
- '000'
department:
- _id: '63'
- _id: '541'
- _id: '178'
- _id: '185'
file:
- access_level: closed
  content_type: application/pdf
  creator: feldi
  date_created: 2018-10-31T17:02:07Z
  date_updated: 2018-10-31T17:02:07Z
  file_id: '5232'
  file_name: TOWARDS A LEAN APPROACH TO GAMIFYING EDUCATION.pdf
  file_size: 485333
  relation: main_file
  success: 1
file_date_updated: 2018-10-31T17:02:07Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://aisel.aisnet.org/ecis2017_rip/46
oa: '1'
page: 2970-2979
publication: Proceedings of the 25th European Conference on Information Systems (ECIS)
status: public
title: Towards a Lean Approach for Gamifying Education
type: conference
user_id: '14052'
year: '2017'
...
---
_id: '11717'
abstract:
- lang: eng
  text: In this work, we address the limited availability of large annotated databases
    for real-life audio event detection by utilizing the concept of transfer learning.
    This technique aims to transfer knowledge from a source domain to a target domain,
    even if source and target have different feature distributions and label sets.
    We hypothesize that all acoustic events share the same inventory of basic acoustic
    building blocks and differ only in the temporal order of these acoustic units.
    We then construct a deep neural network with convolutional layers for extracting
    the acoustic units and a recurrent layer for capturing the temporal order. Under
    the above hypothesis, transfer learning from a source to a target domain with
    a different acoustic event inventory is realized by transferring the convolutional
    layers from the source to the target domain. The recurrent layer is, however,
    learnt directly from the target domain. Experiments on the transfer from a synthetic
    source database to the reallife target database of DCASE 2016 demonstrate that
    transfer learning leads to improved detection performance on average. However,
    the successful transfer to detect events which are very different from what was
    seen in the source domain, could not be verified.
author:
- first_name: Prerna
  full_name: Arora, Prerna
  last_name: Arora
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Arora P, Haeb-Umbach R. A Study on Transfer Learning for Acoustic Event Detection
    in a Real Life Scenario. In: <i>IEEE 19th International Workshop on Multimedia
    Signal Processing (MMSP)</i>. ; 2017.'
  apa: Arora, P., &#38; Haeb-Umbach, R. (2017). A Study on Transfer Learning for Acoustic
    Event Detection in a Real Life Scenario. In <i>IEEE 19th International Workshop
    on Multimedia Signal Processing (MMSP)</i>.
  bibtex: '@inproceedings{Arora_Haeb-Umbach_2017, title={A Study on Transfer Learning
    for Acoustic Event Detection in a Real Life Scenario}, booktitle={IEEE 19th International
    Workshop on Multimedia Signal Processing (MMSP)}, author={Arora, Prerna and Haeb-Umbach,
    Reinhold}, year={2017} }'
  chicago: Arora, Prerna, and Reinhold Haeb-Umbach. “A Study on Transfer Learning
    for Acoustic Event Detection in a Real Life Scenario.” In <i>IEEE 19th International
    Workshop on Multimedia Signal Processing (MMSP)</i>, 2017.
  ieee: P. Arora and R. Haeb-Umbach, “A Study on Transfer Learning for Acoustic Event
    Detection in a Real Life Scenario,” in <i>IEEE 19th International Workshop on
    Multimedia Signal Processing (MMSP)</i>, 2017.
  mla: Arora, Prerna, and Reinhold Haeb-Umbach. “A Study on Transfer Learning for
    Acoustic Event Detection in a Real Life Scenario.” <i>IEEE 19th International
    Workshop on Multimedia Signal Processing (MMSP)</i>, 2017.
  short: 'P. Arora, R. Haeb-Umbach, in: IEEE 19th International Workshop on Multimedia
    Signal Processing (MMSP), 2017.'
date_created: 2019-07-12T05:26:54Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/MMSP_2017_AroraHaeb.pdf
oa: '1'
publication: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2017/MMSP_2017_AroraHaeb_poster.pdf
status: public
title: A Study on Transfer Learning for Acoustic Event Detection in a Real Life Scenario
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11735'
abstract:
- lang: eng
  text: This report describes the computation of gradients by algorithmic differentiation
    for statistically optimum beamforming operations. Especially the derivation of
    complex-valued functions is a key component of this approach. Therefore the real-valued
    algorithmic differentiation is extended via the complex-valued chain rule. In
    addition to the basic mathematic operations the derivative of the eigenvalue problem
    with complex-valued eigenvectors is one of the key results of this report. The
    potential of this approach is shown with experimental results on the CHiME-3 challenge
    database. There, the beamforming task is used as a front-end for an ASR system.
    With the developed derivatives a joint optimization of a speech enhancement and
    speech recognition system w.r.t. the recognition optimization criterion is possible.
author:
- first_name: Christoph
  full_name: Boeddeker, Christoph
  id: '40767'
  last_name: Boeddeker
- first_name: Patrick
  full_name: Hanebrink, Patrick
  last_name: Hanebrink
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Boeddeker C, Hanebrink P, Drude L, Heymann J, Haeb-Umbach R. <i>On the Computation
    of Complex-Valued Gradients with Application to Statistically Optimum Beamforming</i>.;
    2017.
  apa: Boeddeker, C., Hanebrink, P., Drude, L., Heymann, J., &#38; Haeb-Umbach, R.
    (2017). <i>On the Computation of Complex-valued Gradients with Application to
    Statistically Optimum Beamforming</i>.
  bibtex: '@book{Boeddeker_Hanebrink_Drude_Heymann_Haeb-Umbach_2017, title={On the
    Computation of Complex-valued Gradients with Application to Statistically Optimum
    Beamforming}, author={Boeddeker, Christoph and Hanebrink, Patrick and Drude, Lukas
    and Heymann, Jahn and Haeb-Umbach, Reinhold}, year={2017} }'
  chicago: Boeddeker, Christoph, Patrick Hanebrink, Lukas Drude, Jahn Heymann, and
    Reinhold Haeb-Umbach. <i>On the Computation of Complex-Valued Gradients with Application
    to Statistically Optimum Beamforming</i>, 2017.
  ieee: C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, and R. Haeb-Umbach, <i>On
    the Computation of Complex-valued Gradients with Application to Statistically
    Optimum Beamforming</i>. 2017.
  mla: Boeddeker, Christoph, et al. <i>On the Computation of Complex-Valued Gradients
    with Application to Statistically Optimum Beamforming</i>. 2017.
  short: C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, R. Haeb-Umbach, On the
    Computation of Complex-Valued Gradients with Application to Statistically Optimum
    Beamforming, 2017.
date_created: 2019-07-12T05:27:15Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/ArXiv_2017_BoeddekerHanebrinkHaeb_Article.pdf
oa: '1'
status: public
title: On the Computation of Complex-valued Gradients with Application to Statistically
  Optimum Beamforming
type: report
user_id: '40767'
year: '2017'
...
---
_id: '11736'
abstract:
- lang: eng
  text: In this paper we show how a neural network for spectral mask estimation for
    an acoustic beamformer can be optimized by algorithmic differentiation. Using
    the beamformer output SNR as the objective function to maximize, the gradient
    is propagated through the beamformer all the way to the neural network which provides
    the clean speech and noise masks from which the beamformer coefficients are estimated
    by eigenvalue decomposition. A key theoretical result is the derivative of an
    eigenvalue problem involving complex-valued eigenvectors. Experimental results
    on the CHiME-3 challenge database demonstrate the effectiveness of the approach.
    The tools developed in this paper are a key component for an end-to-end optimization
    of speech enhancement and speech recognition.
author:
- first_name: Christoph
  full_name: Boeddeker, Christoph
  id: '40767'
  last_name: Boeddeker
- first_name: Patrick
  full_name: Hanebrink, Patrick
  last_name: Hanebrink
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Boeddeker C, Hanebrink P, Drude L, Heymann J, Haeb-Umbach R. Optimizing Neural-Network
    Supported Acoustic Beamforming by Algorithmic Differentiation. In: <i>Proc. IEEE
    Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)</i>. ; 2017.'
  apa: Boeddeker, C., Hanebrink, P., Drude, L., Heymann, J., &#38; Haeb-Umbach, R.
    (2017). Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic
    Differentiation. In <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal
    Processing (ICASSP)</i>.
  bibtex: '@inproceedings{Boeddeker_Hanebrink_Drude_Heymann_Haeb-Umbach_2017, title={Optimizing
    Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation},
    booktitle={Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)},
    author={Boeddeker, Christoph and Hanebrink, Patrick and Drude, Lukas and Heymann,
    Jahn and Haeb-Umbach, Reinhold}, year={2017} }'
  chicago: Boeddeker, Christoph, Patrick Hanebrink, Lukas Drude, Jahn Heymann, and
    Reinhold Haeb-Umbach. “Optimizing Neural-Network Supported Acoustic Beamforming
    by Algorithmic Differentiation.” In <i>Proc. IEEE Intl. Conf. on Acoustics, Speech
    and Signal Processing (ICASSP)</i>, 2017.
  ieee: C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, and R. Haeb-Umbach, “Optimizing
    Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation,”
    in <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)</i>,
    2017.
  mla: Boeddeker, Christoph, et al. “Optimizing Neural-Network Supported Acoustic
    Beamforming by Algorithmic Differentiation.” <i>Proc. IEEE Intl. Conf. on Acoustics,
    Speech and Signal Processing (ICASSP)</i>, 2017.
  short: 'C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc.
    IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.'
date_created: 2019-07-12T05:27:16Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/icassp_2017_boeddeker_paper.pdf
oa: '1'
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
status: public
title: Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11737'
abstract:
- lang: eng
  text: The benefits of both a logarithmic spectral amplitude (LSA) estimation and
    a modeling in a generalized spectral domain (where short-time amplitudes are raised
    to a generalized power exponent, not restricted to magnitude or power spectrum)
    are combined in this contribution to achieve a better tradeoff between speech
    quality and noise suppression in single-channel speech enhancement. A novel gain
    function is derived to enhance the logarithmic generalized spectral amplitudes
    of noisy speech. Experiments on the CHiME-3 dataset show that it outperforms the
    famous minimum mean squared error (MMSE) LSA gain function of Ephraim and Malah
    in terms of noise suppression by 1.4 dB, while the good speech quality of the
    MMSE-LSA estimator is maintained.
author:
- first_name: Alleksej
  full_name: Chinaev, Alleksej
  last_name: Chinaev
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Chinaev A, Haeb-Umbach R. A Generalized Log-Spectral Amplitude Estimator for
    Single-Channel Speech Enhancement. In: <i>Proc. IEEE Intl. Conf. on Acoustics,
    Speech and Signal Processing (ICASSP)</i>. ; 2017.'
  apa: Chinaev, A., &#38; Haeb-Umbach, R. (2017). A Generalized Log-Spectral Amplitude
    Estimator for Single-Channel Speech Enhancement. In <i>Proc. IEEE Intl. Conf.
    on Acoustics, Speech and Signal Processing (ICASSP)</i>.
  bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2017, title={A Generalized Log-Spectral
    Amplitude Estimator for Single-Channel Speech Enhancement}, booktitle={Proc. IEEE
    Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)}, author={Chinaev,
    Alleksej and Haeb-Umbach, Reinhold}, year={2017} }'
  chicago: Chinaev, Alleksej, and Reinhold Haeb-Umbach. “A Generalized Log-Spectral
    Amplitude Estimator for Single-Channel Speech Enhancement.” In <i>Proc. IEEE Intl.
    Conf. on Acoustics, Speech and Signal Processing (ICASSP)</i>, 2017.
  ieee: A. Chinaev and R. Haeb-Umbach, “A Generalized Log-Spectral Amplitude Estimator
    for Single-Channel Speech Enhancement,” in <i>Proc. IEEE Intl. Conf. on Acoustics,
    Speech and Signal Processing (ICASSP)</i>, 2017.
  mla: Chinaev, Alleksej, and Reinhold Haeb-Umbach. “A Generalized Log-Spectral Amplitude
    Estimator for Single-Channel Speech Enhancement.” <i>Proc. IEEE Intl. Conf. on
    Acoustics, Speech and Signal Processing (ICASSP)</i>, 2017.
  short: 'A. Chinaev, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech
    and Signal Processing (ICASSP), 2017.'
date_created: 2019-07-12T05:27:17Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/ChinHaeb17.pdf
oa: '1'
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
related_material:
  link:
  - description: Slides
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2017/ChinHaeb17_Slides.pdf
status: public
title: A Generalized Log-Spectral Amplitude Estimator for Single-Channel Speech Enhancement
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11754'
abstract:
- lang: eng
  text: Recent advances in discriminatively trained mask estimation networks to extract
    a single source utilizing beamforming techniques demonstrate, that the integration
    of statistical models and deep neural networks (DNNs) are a promising approach
    for robust automatic speech recognition (ASR) applications. In this contribution
    we demonstrate how discriminatively trained embeddings on spectral features can
    be tightly integrated into statistical model-based source separation to separate
    and transcribe overlapping speech. Good generalization to unseen spatial configurations
    is achieved by estimating a statistical model at test time, while still leveraging
    discriminative training of deep clustering embeddings on a separate training set.
    We formulate an expectation maximization (EM) algorithm which jointly estimates
    a model for deep clustering embeddings and complex-valued spatial observations
    in the short time Fourier transform (STFT) domain at test time. Extensive simulations
    confirm, that the integrated model outperforms (a) a deep clustering model with
    a subsequent beamforming step and (b) an EM-based model with a beamforming step
    alone in terms of signal to distortion ratio (SDR) and perceptually motivated
    metric (PESQ) gains. ASR results on a reverberated dataset further show, that
    the aforementioned gains translate to reduced word error rates (WERs) even in
    reverberant environments.
author:
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Drude L, Haeb-Umbach R. Tight integration of spatial and spectral features
    for BSS with Deep Clustering embeddings. In: <i>INTERSPEECH 2017, Stockholm, Schweden</i>.
    ; 2017.'
  apa: Drude, L., &#38; Haeb-Umbach, R. (2017). Tight integration of spatial and spectral
    features for BSS with Deep Clustering embeddings. In <i>INTERSPEECH 2017, Stockholm,
    Schweden</i>.
  bibtex: '@inproceedings{Drude_Haeb-Umbach_2017, title={Tight integration of spatial
    and spectral features for BSS with Deep Clustering embeddings}, booktitle={INTERSPEECH
    2017, Stockholm, Schweden}, author={Drude, Lukas and Haeb-Umbach, Reinhold}, year={2017}
    }'
  chicago: Drude, Lukas, and Reinhold Haeb-Umbach. “Tight Integration of Spatial and
    Spectral Features for BSS with Deep Clustering Embeddings.” In <i>INTERSPEECH
    2017, Stockholm, Schweden</i>, 2017.
  ieee: L. Drude and R. Haeb-Umbach, “Tight integration of spatial and spectral features
    for BSS with Deep Clustering embeddings,” in <i>INTERSPEECH 2017, Stockholm, Schweden</i>,
    2017.
  mla: Drude, Lukas, and Reinhold Haeb-Umbach. “Tight Integration of Spatial and Spectral
    Features for BSS with Deep Clustering Embeddings.” <i>INTERSPEECH 2017, Stockholm,
    Schweden</i>, 2017.
  short: 'L. Drude, R. Haeb-Umbach, in: INTERSPEECH 2017, Stockholm, Schweden, 2017.'
date_created: 2019-07-12T05:27:37Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Drude_paper.pdf
oa: '1'
publication: INTERSPEECH 2017, Stockholm, Schweden
related_material:
  link:
  - description: Slides
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Drude_slides.pdf
status: public
title: Tight integration of spatial and spectral features for BSS with Deep Clustering
  embeddings
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11770'
abstract:
- lang: eng
  text: 'In this contribution we show how to exploit text data to support word discovery
    from audio input in an underresourced target language. Given audio, of which a
    certain amount is transcribed at the word level, and additional unrelated text
    data, the approach is able to learn a probabilistic mapping from acoustic units
    to characters and utilize it to segment the audio data into words without the
    need of a pronunciation dictionary. This is achieved by three components: an unsupervised
    acoustic unit discovery system, a supervisedly trained acoustic unit-to-grapheme
    converter, and a word discovery system, which is initialized with a language model
    trained on the text data. Experiments for multiple setups show that the initialization
    of the language model with text data improves the word segementation performance
    by a large margin.'
author:
- first_name: Thomas
  full_name: Glarner, Thomas
  id: '14169'
  last_name: Glarner
- first_name: Benedikt
  full_name: Boenninghoff, Benedikt
  last_name: Boenninghoff
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Glarner T, Boenninghoff B, Walter O, Haeb-Umbach R. Leveraging Text Data for
    Word Segmentation for Underresourced Languages. In: <i>INTERSPEECH 2017, Stockholm,
    Schweden</i>. ; 2017.'
  apa: Glarner, T., Boenninghoff, B., Walter, O., &#38; Haeb-Umbach, R. (2017). Leveraging
    Text Data for Word Segmentation for Underresourced Languages. In <i>INTERSPEECH
    2017, Stockholm, Schweden</i>.
  bibtex: '@inproceedings{Glarner_Boenninghoff_Walter_Haeb-Umbach_2017, title={Leveraging
    Text Data for Word Segmentation for Underresourced Languages}, booktitle={INTERSPEECH
    2017, Stockholm, Schweden}, author={Glarner, Thomas and Boenninghoff, Benedikt
    and Walter, Oliver and Haeb-Umbach, Reinhold}, year={2017} }'
  chicago: Glarner, Thomas, Benedikt Boenninghoff, Oliver Walter, and Reinhold Haeb-Umbach.
    “Leveraging Text Data for Word Segmentation for Underresourced Languages.” In
    <i>INTERSPEECH 2017, Stockholm, Schweden</i>, 2017.
  ieee: T. Glarner, B. Boenninghoff, O. Walter, and R. Haeb-Umbach, “Leveraging Text
    Data for Word Segmentation for Underresourced Languages,” in <i>INTERSPEECH 2017,
    Stockholm, Schweden</i>, 2017.
  mla: Glarner, Thomas, et al. “Leveraging Text Data for Word Segmentation for Underresourced
    Languages.” <i>INTERSPEECH 2017, Stockholm, Schweden</i>, 2017.
  short: 'T. Glarner, B. Boenninghoff, O. Walter, R. Haeb-Umbach, in: INTERSPEECH
    2017, Stockholm, Schweden, 2017.'
date_created: 2019-07-12T05:27:55Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Glarner_paper.pdf
oa: '1'
publication: INTERSPEECH 2017, Stockholm, Schweden
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Glarner_poster.pdf
status: public
title: Leveraging Text Data for Word Segmentation for Underresourced Languages
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '1180'
abstract:
- lang: eng
  text: These days, there is a strong rise in the needs for machine learning applications,
    requiring an automation of machine learning engineering which is referred to as
    AutoML. In AutoML the selection, composition and parametrization of machine learning
    algorithms is automated and tailored to a specific problem, resulting in a machine
    learning pipeline. Current approaches reduce the AutoML problem to optimization
    of hyperparameters. Based on recursive task networks, in this paper we present
    one approach from the field of automated planning and one evolutionary optimization
    approach. Instead of simply parametrizing a given pipeline, this allows for structure
    optimization of machine learning pipelines, as well. We evaluate the two approaches
    in an extensive evaluation, finding both approaches to have their strengths in
    different areas. Moreover, the two approaches outperform the state-of-the-art
    tool Auto-WEKA in many settings.
author:
- first_name: Marcel Dominik
  full_name: Wever, Marcel Dominik
  id: '33176'
  last_name: Wever
  orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
  full_name: Mohr, Felix
  last_name: Mohr
- first_name: Eyke
  full_name: Hüllermeier, Eyke
  id: '48129'
  last_name: Hüllermeier
citation:
  ama: 'Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning
    Versus Evolutionary Optimization. In: <i>27th Workshop Computational Intelligence</i>.
    Dortmund; 2017.'
  apa: 'Wever, M. D., Mohr, F., &#38; Hüllermeier, E. (2017). Automatic Machine Learning:
    Hierachical Planning Versus Evolutionary Optimization. In <i>27th Workshop Computational
    Intelligence</i>. Dortmund.'
  bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2017, place={Dortmund}, title={Automatic
    Machine Learning: Hierachical Planning Versus Evolutionary Optimization}, booktitle={27th
    Workshop Computational Intelligence}, author={Wever, Marcel Dominik and Mohr,
    Felix and Hüllermeier, Eyke}, year={2017} }'
  chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine
    Learning: Hierachical Planning Versus Evolutionary Optimization.” In <i>27th Workshop
    Computational Intelligence</i>. Dortmund, 2017.'
  ieee: 'M. D. Wever, F. Mohr, and E. Hüllermeier, “Automatic Machine Learning: Hierachical
    Planning Versus Evolutionary Optimization,” in <i>27th Workshop Computational
    Intelligence</i>, Dortmund, 2017.'
  mla: 'Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning
    Versus Evolutionary Optimization.” <i>27th Workshop Computational Intelligence</i>,
    2017.'
  short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence,
    Dortmund, 2017.'
conference:
  end_date: 2017-11-24
  location: Dortmund
  name: 27th Workshop Computational Intelligence
  start_date: 2017-11-23
date_created: 2018-02-22T07:19:18Z
date_updated: 2022-01-06T06:51:09Z
ddc:
- '000'
department:
- _id: '355'
file:
- access_level: closed
  content_type: application/pdf
  creator: wever
  date_created: 2018-11-06T15:28:09Z
  date_updated: 2018-11-06T15:28:09Z
  file_id: '5387'
  file_name: CI Workshop AutoML.pdf
  file_size: 323589
  relation: main_file
  success: 1
file_date_updated: 2018-11-06T15:28:09Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://publikationen.bibliothek.kit.edu/1000074341/4643874
oa: '1'
place: Dortmund
project:
- _id: '1'
  name: SFB 901
- _id: '3'
  name: SFB 901 - Project Area B
- _id: '10'
  name: SFB 901 - Subproject B2
publication: 27th Workshop Computational Intelligence
publication_status: published
status: public
title: 'Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization'
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '11809'
abstract:
- lang: eng
  text: This paper presents an end-to-end training approach for a beamformer-supported
    multi-channel ASR system. A neural network which estimates masks for a statistically
    optimum beamformer is jointly trained with a network for acoustic modeling. To
    update its parameters, we propagate the gradients from the acoustic model all
    the way through feature extraction and the complex valued beamforming operation.
    Besides avoiding a mismatch between the front-end and the back-end, this approach
    also eliminates the need for stereo data, i.e., the parallel availability of clean
    and noisy versions of the signals. Instead, it can be trained with real noisy
    multichannel data only. Also, relying on the signal statistics for beamforming,
    the approach makes no assumptions on the configuration of the microphone array.
    We further observe a performance gain through joint training in terms of word
    error rate in an evaluation of the system on the CHiME 4 dataset.
author:
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Christoph
  full_name: Boeddeker, Christoph
  id: '40767'
  last_name: Boeddeker
- first_name: Patrick
  full_name: Hanebrink, Patrick
  last_name: Hanebrink
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Heymann J, Drude L, Boeddeker C, Hanebrink P, Haeb-Umbach R. BEAMNET: End-to-End
    Training of a Beamformer-Supported Multi-Channel ASR System. In: <i>Proc. IEEE
    Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)</i>. ; 2017.'
  apa: 'Heymann, J., Drude, L., Boeddeker, C., Hanebrink, P., &#38; Haeb-Umbach, R.
    (2017). BEAMNET: End-to-End Training of a Beamformer-Supported Multi-Channel ASR
    System. In <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing
    (ICASSP)</i>.'
  bibtex: '@inproceedings{Heymann_Drude_Boeddeker_Hanebrink_Haeb-Umbach_2017, title={BEAMNET:
    End-to-End Training of a Beamformer-Supported Multi-Channel ASR System}, booktitle={Proc.
    IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)}, author={Heymann,
    Jahn and Drude, Lukas and Boeddeker, Christoph and Hanebrink, Patrick and Haeb-Umbach,
    Reinhold}, year={2017} }'
  chicago: 'Heymann, Jahn, Lukas Drude, Christoph Boeddeker, Patrick Hanebrink, and
    Reinhold Haeb-Umbach. “BEAMNET: End-to-End Training of a Beamformer-Supported
    Multi-Channel ASR System.” In <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and
    Signal Processing (ICASSP)</i>, 2017.'
  ieee: 'J. Heymann, L. Drude, C. Boeddeker, P. Hanebrink, and R. Haeb-Umbach, “BEAMNET:
    End-to-End Training of a Beamformer-Supported Multi-Channel ASR System,” in <i>Proc.
    IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)</i>, 2017.'
  mla: 'Heymann, Jahn, et al. “BEAMNET: End-to-End Training of a Beamformer-Supported
    Multi-Channel ASR System.” <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and
    Signal Processing (ICASSP)</i>, 2017.'
  short: 'J. Heymann, L. Drude, C. Boeddeker, P. Hanebrink, R. Haeb-Umbach, in: Proc.
    IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.'
date_created: 2019-07-12T05:28:40Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/icassp_2017_heymann_paper.pdf
oa: '1'
project:
- _id: '52'
  name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2017/icassp_2017_heymann_poster.pdf
status: public
title: 'BEAMNET: End-to-End Training of a Beamformer-Supported Multi-Channel ASR System'
type: conference
user_id: '40767'
year: '2017'
...
---
_id: '11811'
abstract:
- lang: eng
  text: 'Acoustic beamforming can greatly improve the performance of Automatic Speech
    Recognition (ASR) and speech enhancement systems when multiple channels are available.
    We recently proposed a way to support the model-based Generalized Eigenvalue beamforming
    operation with a powerful neural network for spectral mask estimation. The enhancement
    system has a number of desirable properties. In particular, neither assumptions
    need to be made about the nature of the acoustic transfer function (e.g., being
    anechonic), nor does the array configuration need to be known. While the system
    has been originally developed to enhance speech in noisy environments, we show
    in this article that it is also effective in suppressing reverberation, thus leading
    to a generic trainable multi-channel speech enhancement system for robust speech
    processing. To support this claim, we consider two distinct datasets: The CHiME
    3 challenge, which features challenging real-world noise distortions, and the
    Reverb challenge, which focuses on distortions caused by reverberation. We evaluate
    the system both with respect to a speech enhancement and a recognition task. For
    the first task we propose a new way to cope with the distortions introduced by
    the Generalized Eigenvalue beamformer by renormalizing the target energy for each
    frequency bin, and measure its effectiveness in terms of the PESQ score. For the
    latter we feed the enhanced signal to a strong DNN back-end and achieve state-of-the-art
    ASR results on both datasets. We further experiment with different network architectures
    for spectral mask estimation: One small feed-forward network with only one hidden
    layer, one Convolutional Neural Network and one bi-directional Long Short-Term
    Memory network, showing that even a small network is capable of delivering significant
    performance improvements.'
author:
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Heymann J, Drude L, Haeb-Umbach R. A Generic Neural Acoustic Beamforming Architecture
    for Robust Multi-Channel Speech Processing. <i>Computer Speech and Language</i>.
    2017.
  apa: Heymann, J., Drude, L., &#38; Haeb-Umbach, R. (2017). A Generic Neural Acoustic
    Beamforming Architecture for Robust Multi-Channel Speech Processing. <i>Computer
    Speech and Language</i>.
  bibtex: '@article{Heymann_Drude_Haeb-Umbach_2017, title={A Generic Neural Acoustic
    Beamforming Architecture for Robust Multi-Channel Speech Processing}, journal={Computer
    Speech and Language}, author={Heymann, Jahn and Drude, Lukas and Haeb-Umbach,
    Reinhold}, year={2017} }'
  chicago: Heymann, Jahn, Lukas Drude, and Reinhold Haeb-Umbach. “A Generic Neural
    Acoustic Beamforming Architecture for Robust Multi-Channel Speech Processing.”
    <i>Computer Speech and Language</i>, 2017.
  ieee: J. Heymann, L. Drude, and R. Haeb-Umbach, “A Generic Neural Acoustic Beamforming
    Architecture for Robust Multi-Channel Speech Processing,” <i>Computer Speech and
    Language</i>, 2017.
  mla: Heymann, Jahn, et al. “A Generic Neural Acoustic Beamforming Architecture for
    Robust Multi-Channel Speech Processing.” <i>Computer Speech and Language</i>,
    2017.
  short: J. Heymann, L. Drude, R. Haeb-Umbach, Computer Speech and Language (2017).
date_created: 2019-07-12T05:28:43Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/ComputerSpeechLanguage_2017_heymann_paper.pdf
oa: '1'
publication: Computer Speech and Language
status: public
title: A Generic Neural Acoustic Beamforming Architecture for Robust Multi-Channel
  Speech Processing
type: journal_article
user_id: '44006'
year: '2017'
...
---
_id: '119'
author:
- first_name: Marcel Dominik
  full_name: Wever, Marcel Dominik
  id: '33176'
  last_name: Wever
  orcid: ' https://orcid.org/0000-0001-9782-6818'
citation:
  ama: Wever MD. <i>Active Learning of User Requirement Specifications in Dynamic
    Software Service Markets</i>. Universität Paderborn; 2017.
  apa: Wever, M. D. (2017). <i>Active Learning of User Requirement Specifications
    in Dynamic Software Service Markets</i>. Universität Paderborn.
  bibtex: '@book{Wever_2017, title={Active Learning of User Requirement Specifications
    in Dynamic Software Service Markets}, publisher={Universität Paderborn}, author={Wever,
    Marcel Dominik}, year={2017} }'
  chicago: Wever, Marcel Dominik. <i>Active Learning of User Requirement Specifications
    in Dynamic Software Service Markets</i>. Universität Paderborn, 2017.
  ieee: M. D. Wever, <i>Active Learning of User Requirement Specifications in Dynamic
    Software Service Markets</i>. Universität Paderborn, 2017.
  mla: Wever, Marcel Dominik. <i>Active Learning of User Requirement Specifications
    in Dynamic Software Service Markets</i>. Universität Paderborn, 2017.
  short: M.D. Wever, Active Learning of User Requirement Specifications in Dynamic
    Software Service Markets, Universität Paderborn, 2017.
date_created: 2017-10-17T12:41:14Z
date_updated: 2022-01-06T06:51:12Z
ddc:
- '000'
file:
- access_level: open_access
  content_type: application/pdf
  creator: wever
  date_created: 2018-11-06T15:31:48Z
  date_updated: 2020-07-16T11:53:45Z
  file_id: '5388'
  file_name: MT-export-2017-03-17.pdf
  file_size: 4012186
  relation: main_file
file_date_updated: 2020-07-16T11:53:45Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '1'
  name: SFB 901
- _id: '9'
  name: SFB 901 - Subprojekt B1
- _id: '3'
  name: SFB 901 - Project Area B
publisher: Universität Paderborn
status: public
title: Active Learning of User Requirement Specifications in Dynamic Software Service
  Markets
type: mastersthesis
user_id: '33176'
year: '2017'
...
---
_id: '15912'
author:
- first_name: Martin
  full_name: Grothe, Martin
  last_name: Grothe
- first_name: Tobias
  full_name: Niemann, Tobias
  last_name: Niemann
- first_name: Juraj
  full_name: Somorovsky, Juraj
  id: '83504'
  last_name: Somorovsky
  orcid: 0000-0002-3593-7720
- first_name: Jörg
  full_name: Schwenk, Jörg
  last_name: Schwenk
citation:
  ama: 'Grothe M, Niemann T, Somorovsky J, Schwenk J. Breaking and Fixing Gridcoin.
    In: <i>11th {USENIX} Workshop on Offensive Technologies ({WOOT} 17)</i>. Vancouver,
    BC: {USENIX} Association; 2017.'
  apa: 'Grothe, M., Niemann, T., Somorovsky, J., &#38; Schwenk, J. (2017). Breaking
    and Fixing Gridcoin. In <i>11th {USENIX} Workshop on Offensive Technologies ({WOOT}
    17)</i>. Vancouver, BC: {USENIX} Association.'
  bibtex: '@inproceedings{Grothe_Niemann_Somorovsky_Schwenk_2017, place={Vancouver,
    BC}, title={Breaking and Fixing Gridcoin}, booktitle={11th {USENIX} Workshop on
    Offensive Technologies ({WOOT} 17)}, publisher={{USENIX} Association}, author={Grothe,
    Martin and Niemann, Tobias and Somorovsky, Juraj and Schwenk, Jörg}, year={2017}
    }'
  chicago: 'Grothe, Martin, Tobias Niemann, Juraj Somorovsky, and Jörg Schwenk. “Breaking
    and Fixing Gridcoin.” In <i>11th {USENIX} Workshop on Offensive Technologies ({WOOT}
    17)</i>. Vancouver, BC: {USENIX} Association, 2017.'
  ieee: M. Grothe, T. Niemann, J. Somorovsky, and J. Schwenk, “Breaking and Fixing
    Gridcoin,” in <i>11th {USENIX} Workshop on Offensive Technologies ({WOOT} 17)</i>,
    2017.
  mla: Grothe, Martin, et al. “Breaking and Fixing Gridcoin.” <i>11th {USENIX} Workshop
    on Offensive Technologies ({WOOT} 17)</i>, {USENIX} Association, 2017.
  short: 'M. Grothe, T. Niemann, J. Somorovsky, J. Schwenk, in: 11th {USENIX} Workshop
    on Offensive Technologies ({WOOT} 17), {USENIX} Association, Vancouver, BC, 2017.'
date_created: 2020-02-15T10:05:49Z
date_updated: 2022-01-06T06:52:40Z
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.usenix.org/conference/woot17/workshop-program/presentation/grothe
oa: '1'
place: Vancouver, BC
publication: 11th {USENIX} Workshop on Offensive Technologies ({WOOT} 17)
publisher: '{USENIX} Association'
status: public
title: Breaking and Fixing Gridcoin
type: conference
user_id: '83504'
year: '2017'
...
---
_id: '10206'
author:
- first_name: Felix
  full_name: Mohr, Felix
  last_name: Mohr
- first_name: Theodor
  full_name: Lettmann, Theodor
  id: '315'
  last_name: Lettmann
  orcid: 0000-0001-5859-2457
- first_name: Eyke
  full_name: Hüllermeier, Eyke
  id: '48129'
  last_name: Hüllermeier
citation:
  ama: 'Mohr F, Lettmann T, Hüllermeier E. Planning with Independent Task Networks.
    In: <i>Proc. 40th Annual German Conference on Advances in Artificial Intelligence
    (KI 2017)</i>. ; 2017:193-206. doi:<a href="https://doi.org/10.1007/978-3-319-67190-1_15">10.1007/978-3-319-67190-1_15</a>'
  apa: Mohr, F., Lettmann, T., &#38; Hüllermeier, E. (2017). Planning with Independent
    Task Networks. In <i>Proc. 40th Annual German Conference on Advances in Artificial
    Intelligence (KI 2017)</i> (pp. 193–206). <a href="https://doi.org/10.1007/978-3-319-67190-1_15">https://doi.org/10.1007/978-3-319-67190-1_15</a>
  bibtex: '@inproceedings{Mohr_Lettmann_Hüllermeier_2017, title={Planning with Independent
    Task Networks}, DOI={<a href="https://doi.org/10.1007/978-3-319-67190-1_15">10.1007/978-3-319-67190-1_15</a>},
    booktitle={Proc. 40th Annual German Conference on Advances in Artificial Intelligence
    (KI 2017)}, author={Mohr, Felix and Lettmann, Theodor and Hüllermeier, Eyke},
    year={2017}, pages={193–206} }'
  chicago: Mohr, Felix, Theodor Lettmann, and Eyke Hüllermeier. “Planning with Independent
    Task Networks.” In <i>Proc. 40th Annual German Conference on Advances in Artificial
    Intelligence (KI 2017)</i>, 193–206, 2017. <a href="https://doi.org/10.1007/978-3-319-67190-1_15">https://doi.org/10.1007/978-3-319-67190-1_15</a>.
  ieee: F. Mohr, T. Lettmann, and E. Hüllermeier, “Planning with Independent Task
    Networks,” in <i>Proc. 40th Annual German Conference on Advances in Artificial
    Intelligence (KI 2017)</i>, 2017, pp. 193–206.
  mla: Mohr, Felix, et al. “Planning with Independent Task Networks.” <i>Proc. 40th
    Annual German Conference on Advances in Artificial Intelligence (KI 2017)</i>,
    2017, pp. 193–206, doi:<a href="https://doi.org/10.1007/978-3-319-67190-1_15">10.1007/978-3-319-67190-1_15</a>.
  short: 'F. Mohr, T. Lettmann, E. Hüllermeier, in: Proc. 40th Annual German Conference
    on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206.'
date_created: 2019-06-07T15:24:16Z
date_updated: 2022-01-06T06:50:31Z
ddc:
- '000'
department:
- _id: '7'
- _id: '34'
- _id: '355'
doi: 10.1007/978-3-319-67190-1_15
file:
- access_level: open_access
  content_type: application/pdf
  creator: lettmann
  date_created: 2020-02-28T12:50:18Z
  date_updated: 2020-02-28T12:50:18Z
  file_id: '16157'
  file_name: ki17.pdf
  file_size: 374421
  relation: main_file
file_date_updated: 2020-02-28T12:50:18Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 193-206
publication: Proc. 40th Annual German Conference on Advances in Artificial Intelligence
  (KI 2017)
status: public
title: Planning with Independent Task Networks
type: conference
user_id: '315'
year: '2017'
...
---
_id: '30148'
author:
- first_name: Elena
  full_name: Ficara, Elena
  id: '35768'
  last_name: Ficara
citation:
  ama: Ficara E. Was ist Synthese? <i>Fatum Magazin</i>. 2017;6:9.
  apa: Ficara, E. (2017). Was ist Synthese? <i>Fatum Magazin</i>, <i>6</i>, 9.
  bibtex: '@article{Ficara_2017, title={Was ist Synthese?}, volume={6}, journal={Fatum
    Magazin}, author={Ficara, Elena}, year={2017}, pages={9} }'
  chicago: 'Ficara, Elena. “Was ist Synthese?” <i>Fatum Magazin</i> 6 (2017): 9.'
  ieee: E. Ficara, “Was ist Synthese?,” <i>Fatum Magazin</i>, vol. 6, p. 9, 2017.
  mla: Ficara, Elena. “Was ist Synthese?” <i>Fatum Magazin</i>, vol. 6, 2017, p. 9.
  short: E. Ficara, Fatum Magazin 6 (2017) 9.
date_created: 2022-02-27T19:46:01Z
date_updated: 2022-03-01T12:04:47Z
intvolume: '         6'
language:
- iso: ger
main_file_link:
- open_access: '1'
  url: https://www.fatum-magazin.de/ausgaben/synthese/was-ist-das-synthese/antwort-von-elena-ficara.html
oa: '1'
page: '9'
publication: Fatum Magazin
status: public
title: Was ist Synthese?
type: journal_article
user_id: '35768'
volume: 6
year: '2017'
...
---
_id: '29930'
author:
- first_name: Markus
  full_name: Ott, Markus
  last_name: Ott
- first_name: Alexander
  full_name: Beckmann, Alexander
  last_name: Beckmann
- first_name: Joachim
  full_name: Böcker, Joachim
  id: '66'
  last_name: Böcker
  orcid: 0000-0002-8480-7295
citation:
  ama: 'Ott M, Beckmann A, Böcker J. A Compensation Method for Production Tolerances
    in Electric Drive Systems Using an Extended Open-Loop Torque Control. In: <i>European
    Battery, Hybrid and Fuel Cell Electric Vehicle Congress Geneva, 14th-16th March
    2017</i>. ; 2017.'
  apa: Ott, M., Beckmann, A., &#38; Böcker, J. (2017). A Compensation Method for Production
    Tolerances in Electric Drive Systems Using an Extended Open-Loop Torque Control.
    <i>European Battery, Hybrid and Fuel Cell Electric Vehicle Congress Geneva, 14th-16th
    March 2017</i>. European Battery, Hybrid and Fuel Cell Electric Vehicle Congress,
    Geneva, Switzerland.
  bibtex: '@inproceedings{Ott_Beckmann_Böcker_2017, title={A Compensation Method for
    Production Tolerances in Electric Drive Systems Using an Extended Open-Loop Torque
    Control}, booktitle={European Battery, Hybrid and Fuel Cell Electric Vehicle Congress
    Geneva, 14th-16th March 2017}, author={Ott, Markus and Beckmann, Alexander and
    Böcker, Joachim}, year={2017} }'
  chicago: Ott, Markus, Alexander Beckmann, and Joachim Böcker. “A Compensation Method
    for Production Tolerances in Electric Drive Systems Using an Extended Open-Loop
    Torque Control.” In <i>European Battery, Hybrid and Fuel Cell Electric Vehicle
    Congress Geneva, 14th-16th March 2017</i>, 2017.
  ieee: M. Ott, A. Beckmann, and J. Böcker, “A Compensation Method for Production
    Tolerances in Electric Drive Systems Using an Extended Open-Loop Torque Control,”
    presented at the European Battery, Hybrid and Fuel Cell Electric Vehicle Congress,
    Geneva, Switzerland, 2017.
  mla: Ott, Markus, et al. “A Compensation Method for Production Tolerances in Electric
    Drive Systems Using an Extended Open-Loop Torque Control.” <i>European Battery,
    Hybrid and Fuel Cell Electric Vehicle Congress Geneva, 14th-16th March 2017</i>,
    2017.
  short: 'M. Ott, A. Beckmann, J. Böcker, in: European Battery, Hybrid and Fuel Cell
    Electric Vehicle Congress Geneva, 14th-16th March 2017, 2017.'
conference:
  location: Geneva, Switzerland
  name: European Battery, Hybrid and Fuel Cell Electric Vehicle Congress
  start_date: 2017-03
date_created: 2022-02-21T12:58:24Z
date_updated: 2022-03-02T08:20:59Z
ddc:
- '620'
department:
- _id: '34'
- _id: '52'
file:
- access_level: open_access
  content_type: application/pdf
  creator: boecker
  date_created: 2022-02-21T12:56:13Z
  date_updated: 2022-03-02T08:20:59Z
  file_id: '29932'
  file_name: 2017-Ott-Beckmann-Boecker.pdf
  file_size: 1226838
  relation: main_file
file_date_updated: 2022-03-02T08:20:59Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
publication: European Battery, Hybrid and Fuel Cell Electric Vehicle Congress Geneva,
  14th-16th March 2017
status: public
title: A Compensation Method for Production Tolerances in Electric Drive Systems Using
  an Extended Open-Loop Torque Control
type: conference
user_id: '66'
year: '2017'
...