---
_id: '24024'
abstract:
- lang: eng
text: Recently it has been demonstrated that an optoelectronic phase-locked loop
(OEPLL) using a mode-locked laser as a reference oscillator achieves significantly
lower phase noise than conventional electronic frequency synthesizers. In this
paper a concept for an OEPLL-based frequency synthesizer is presented and it is
investigated how it can be used as a local oscillator (LO) for THz transceivers
in order to improve the signal quality in THz wireless communications. The concept
of the OEPLL is presented and it's measured phase noise is compared to the phase
noise of a laboratory-grade electronic frequency synthesizer. The measured phase
noise spectra of both synthesizers at 10 GHz are then used to model LO phase noise
at 320 GHz. Based on models of generic zero-IF transmit and receive frontends,
THz signals with different modulation formats and Baud rates are simulated at
system level using the modeled LO phase noise for the two LO approaches. Finally,
the results are compared.
author:
- first_name: Christoph
full_name: Scheytt, Christoph
id: '37144'
last_name: Scheytt
orcid: https://orcid.org/0000-0002-5950-6618
- first_name: Dominik
full_name: Wrana, Dominik
last_name: Wrana
- first_name: Meysam
full_name: Bahmanian, Meysam
id: '69233'
last_name: Bahmanian
- first_name: Ingmar
full_name: Kallfass, Ingmar
last_name: Kallfass
citation:
ama: 'Scheytt C, Wrana D, Bahmanian M, Kallfass I. Ultra-Low Phase Noise Frequency
Synthesis for THz Communications Using Optoelectronic PLLs. In: 2020 Third
International Workshop on Mobile Terahertz Systems (IWMTS). ; 2020. doi:10.1109/IWMTS49292.2020.9166347'
apa: Scheytt, C., Wrana, D., Bahmanian, M., & Kallfass, I. (2020). Ultra-Low
Phase Noise Frequency Synthesis for THz Communications Using Optoelectronic PLLs.
2020 Third International Workshop on Mobile Terahertz Systems (IWMTS).
https://doi.org/10.1109/IWMTS49292.2020.9166347
bibtex: '@inproceedings{Scheytt_Wrana_Bahmanian_Kallfass_2020, title={Ultra-Low
Phase Noise Frequency Synthesis for THz Communications Using Optoelectronic PLLs},
DOI={10.1109/IWMTS49292.2020.9166347},
booktitle={2020 Third International Workshop on Mobile Terahertz Systems (IWMTS)},
author={Scheytt, Christoph and Wrana, Dominik and Bahmanian, Meysam and Kallfass,
Ingmar}, year={2020} }'
chicago: Scheytt, Christoph, Dominik Wrana, Meysam Bahmanian, and Ingmar Kallfass.
“Ultra-Low Phase Noise Frequency Synthesis for THz Communications Using Optoelectronic
PLLs.” In 2020 Third International Workshop on Mobile Terahertz Systems (IWMTS),
2020. https://doi.org/10.1109/IWMTS49292.2020.9166347.
ieee: 'C. Scheytt, D. Wrana, M. Bahmanian, and I. Kallfass, “Ultra-Low Phase Noise
Frequency Synthesis for THz Communications Using Optoelectronic PLLs,” Essen,
Germany , 2020, doi: 10.1109/IWMTS49292.2020.9166347.'
mla: Scheytt, Christoph, et al. “Ultra-Low Phase Noise Frequency Synthesis for THz
Communications Using Optoelectronic PLLs.” 2020 Third International Workshop
on Mobile Terahertz Systems (IWMTS), 2020, doi:10.1109/IWMTS49292.2020.9166347.
short: 'C. Scheytt, D. Wrana, M. Bahmanian, I. Kallfass, in: 2020 Third International
Workshop on Mobile Terahertz Systems (IWMTS), 2020.'
conference:
end_date: 2020.07.02
location: 'Essen, Germany '
start_date: 2020.07.01
date_created: 2021-09-09T11:50:15Z
date_updated: 2023-01-11T07:18:47Z
department:
- _id: '58'
- _id: '230'
doi: 10.1109/IWMTS49292.2020.9166347
language:
- iso: eng
publication: 2020 Third International Workshop on Mobile Terahertz Systems (IWMTS)
related_material:
link:
- relation: confirmation
url: https://ieeexplore.ieee.org/document/9166347
status: public
title: Ultra-Low Phase Noise Frequency Synthesis for THz Communications Using Optoelectronic
PLLs
type: conference
user_id: '15931'
year: '2020'
...
---
_id: '13226'
abstract:
- lang: eng
text: "The canonical problem for the class Quantum Merlin-Arthur (QMA) is that of\r\nestimating
ground state energies of local Hamiltonians. Perhaps surprisingly,\r\n[Ambainis,
CCC 2014] showed that the related, but arguably more natural,\r\nproblem of simulating
local measurements on ground states of local Hamiltonians\r\n(APX-SIM) is likely
harder than QMA. Indeed, [Ambainis, CCC 2014] showed that\r\nAPX-SIM is P^QMA[log]-complete,
for P^QMA[log] the class of languages decidable\r\nby a P machine making a logarithmic
number of adaptive queries to a QMA oracle.\r\nIn this work, we show that APX-SIM
is P^QMA[log]-complete even when restricted\r\nto more physical Hamiltonians,
obtaining as intermediate steps a variety of\r\nrelated complexity-theoretic results.\r\n
\ We first give a sequence of results which together yield P^QMA[log]-hardness\r\nfor
APX-SIM on well-motivated Hamiltonians: (1) We show that for NP, StoqMA,\r\nand
QMA oracles, a logarithmic number of adaptive queries is equivalent to\r\npolynomially
many parallel queries. These equalities simplify the proofs of our\r\nsubsequent
results. (2) Next, we show that the hardness of APX-SIM is preserved\r\nunder
Hamiltonian simulations (a la [Cubitt, Montanaro, Piddock, 2017]). As a\r\nbyproduct,
we obtain a full complexity classification of APX-SIM, showing it is\r\ncomplete
for P, P^||NP, P^||StoqMA, or P^||QMA depending on the Hamiltonians\r\nemployed.
(3) Leveraging the above, we show that APX-SIM is P^QMA[log]-complete\r\nfor any
family of Hamiltonians which can efficiently simulate spatially sparse\r\nHamiltonians,
including physically motivated models such as the 2D Heisenberg\r\nmodel.\r\n
\ Our second focus considers 1D systems: We show that APX-SIM remains\r\nP^QMA[log]-complete
even for local Hamiltonians on a 1D line of 8-dimensional\r\nqudits. This uses
a number of ideas from above, along with replacing the \"query\r\nHamiltonian\"
of [Ambainis, CCC 2014] with a new \"sifter\" construction."
author:
- first_name: Sevag
full_name: Gharibian, Sevag
id: '71541'
last_name: Gharibian
orcid: 0000-0002-9992-3379
- first_name: Stephen
full_name: Piddock, Stephen
last_name: Piddock
- first_name: Justin
full_name: Yirka, Justin
last_name: Yirka
citation:
ama: 'Gharibian S, Piddock S, Yirka J. Oracle complexity classes and local measurements
on physical Hamiltonians. In: Proceedings of the 37th Symposium on Theoretical
Aspects of Computer Science (STACS 2020). ; 2020:38.'
apa: Gharibian, S., Piddock, S., & Yirka, J. (2020). Oracle complexity classes
and local measurements on physical Hamiltonians. Proceedings of the 37th Symposium
on Theoretical Aspects of Computer Science (STACS 2020), 38.
bibtex: '@inproceedings{Gharibian_Piddock_Yirka_2020, title={Oracle complexity classes
and local measurements on physical Hamiltonians}, booktitle={Proceedings of the
37th Symposium on Theoretical Aspects of Computer Science (STACS 2020)}, author={Gharibian,
Sevag and Piddock, Stephen and Yirka, Justin}, year={2020}, pages={38} }'
chicago: Gharibian, Sevag, Stephen Piddock, and Justin Yirka. “Oracle Complexity
Classes and Local Measurements on Physical Hamiltonians.” In Proceedings of
the 37th Symposium on Theoretical Aspects of Computer Science (STACS 2020),
38, 2020.
ieee: S. Gharibian, S. Piddock, and J. Yirka, “Oracle complexity classes and local
measurements on physical Hamiltonians,” in Proceedings of the 37th Symposium
on Theoretical Aspects of Computer Science (STACS 2020), 2020, p. 38.
mla: Gharibian, Sevag, et al. “Oracle Complexity Classes and Local Measurements
on Physical Hamiltonians.” Proceedings of the 37th Symposium on Theoretical
Aspects of Computer Science (STACS 2020), 2020, p. 38.
short: 'S. Gharibian, S. Piddock, J. Yirka, in: Proceedings of the 37th Symposium
on Theoretical Aspects of Computer Science (STACS 2020), 2020, p. 38.'
date_created: 2019-09-16T07:41:31Z
date_updated: 2023-10-09T04:17:41Z
department:
- _id: '623'
- _id: '7'
external_id:
arxiv:
- '1909.05981'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1909.05981
oa: '1'
page: '38'
publication: Proceedings of the 37th Symposium on Theoretical Aspects of Computer
Science (STACS 2020)
publication_status: published
status: public
title: Oracle complexity classes and local measurements on physical Hamiltonians
type: conference
user_id: '71541'
year: '2020'
...
---
_id: '46319'
abstract:
- lang: eng
text: The detection of orchestrated and potentially manipulative campaigns in social
media is far more meaningful than an- alyzing single account behaviour but also
more challenging in terms of pattern recognition, data processing, and com- putational
complexity. While supervised learning methods need an enormous amount of reliable
ground truth data to find rather inflexible patterns, classical unsupervised learn-
ing techniques need a lot of computational power to handle large amount of data.
This makes them infeasible for real- time analysis. In this work, we demonstrate
the applicability of text stream clustering for the real-time detection of coordi-
nated campaigns.
author:
- first_name: D
full_name: Assenmacher, D
last_name: Assenmacher
- first_name: L
full_name: Adam, L
last_name: Adam
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: C
full_name: Grimme, C
last_name: Grimme
citation:
ama: 'Assenmacher D, Adam L, Trautmann H, Grimme C. Towards Real-Time and Unsupervised
Campaign Detection in Social Media. In: Proceedings of the Florida Artificial
Intelligence Research Society Conference. ; 2020.'
apa: Assenmacher, D., Adam, L., Trautmann, H., & Grimme, C. (2020). Towards
Real-Time and Unsupervised Campaign Detection in Social Media. Proceedings
of the Florida Artificial Intelligence Research Society Conference.
bibtex: '@inproceedings{Assenmacher_Adam_Trautmann_Grimme_2020, place={Florida,
USA}, title={Towards Real-Time and Unsupervised Campaign Detection in Social Media},
booktitle={Proceedings of the Florida Artificial Intelligence Research Society
Conference}, author={Assenmacher, D and Adam, L and Trautmann, Heike and Grimme,
C}, year={2020} }'
chicago: Assenmacher, D, L Adam, Heike Trautmann, and C Grimme. “Towards Real-Time
and Unsupervised Campaign Detection in Social Media.” In Proceedings of the
Florida Artificial Intelligence Research Society Conference. Florida, USA,
2020.
ieee: D. Assenmacher, L. Adam, H. Trautmann, and C. Grimme, “Towards Real-Time and
Unsupervised Campaign Detection in Social Media,” 2020.
mla: Assenmacher, D., et al. “Towards Real-Time and Unsupervised Campaign Detection
in Social Media.” Proceedings of the Florida Artificial Intelligence Research
Society Conference, 2020.
short: 'D. Assenmacher, L. Adam, H. Trautmann, C. Grimme, in: Proceedings of the
Florida Artificial Intelligence Research Society Conference, Florida, USA, 2020.'
date_created: 2023-08-04T07:29:36Z
date_updated: 2023-10-16T12:59:10Z
department:
- _id: '34'
- _id: '819'
language:
- iso: eng
place: Florida, USA
publication: Proceedings of the Florida Artificial Intelligence Research Society Conference
status: public
title: Towards Real-Time and Unsupervised Campaign Detection in Social Media
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '20505'
abstract:
- lang: eng
text: "Speech activity detection (SAD), which often rests on the fact that the noise
is \"more'' stationary than speech, is particularly challenging in non-stationary
environments, because the time variance of the acoustic scene makes it difficult
to discriminate speech from noise. We propose two approaches to SAD, where one
is based on statistical signal processing, while the other utilizes neural networks.
The former employs sophisticated signal processing to track the noise and speech
energies and is meant to support the case for a resource efficient, unsupervised
signal processing approach.\r\nThe latter introduces a recurrent network layer
that operates on short segments of the input speech to do temporal smoothing in
the presence of non-stationary noise. The systems are tested on the Fearless Steps
challenge database, which consists of the transmission data from the Apollo-11
space mission.\r\nThe statistical SAD achieves comparable detection performance
to earlier proposed neural network based SADs, while the neural network based
approach leads to a decision cost function of 1.07% on the evaluation set of the
2020 Fearless Steps Challenge, which sets a new state of the art."
author:
- first_name: Jens
full_name: Heitkaemper, Jens
id: '27643'
last_name: Heitkaemper
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Heitkaemper J, Schmalenstroeer J, Haeb-Umbach R. Statistical and Neural Network
Based Speech Activity Detection in Non-Stationary Acoustic Environments. In: INTERSPEECH
2020 Virtual Shanghai China. ; 2020.'
apa: Heitkaemper, J., Schmalenstroeer, J., & Haeb-Umbach, R. (2020). Statistical
and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic
Environments. INTERSPEECH 2020 Virtual Shanghai China.
bibtex: '@inproceedings{Heitkaemper_Schmalenstroeer_Haeb-Umbach_2020, title={Statistical
and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic
Environments}, booktitle={INTERSPEECH 2020 Virtual Shanghai China}, author={Heitkaemper,
Jens and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2020} }'
chicago: Heitkaemper, Jens, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Statistical
and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic
Environments.” In INTERSPEECH 2020 Virtual Shanghai China, 2020.
ieee: J. Heitkaemper, J. Schmalenstroeer, and R. Haeb-Umbach, “Statistical and Neural
Network Based Speech Activity Detection in Non-Stationary Acoustic Environments,”
2020.
mla: Heitkaemper, Jens, et al. “Statistical and Neural Network Based Speech Activity
Detection in Non-Stationary Acoustic Environments.” INTERSPEECH 2020 Virtual
Shanghai China, 2020.
short: 'J. Heitkaemper, J. Schmalenstroeer, R. Haeb-Umbach, in: INTERSPEECH 2020
Virtual Shanghai China, 2020.'
date_created: 2020-11-25T15:03:19Z
date_updated: 2023-10-26T08:28:49Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: closed
content_type: application/pdf
creator: jensheit
date_created: 2020-12-11T12:33:04Z
date_updated: 2020-12-11T12:33:04Z
file_id: '20697'
file_name: ms.pdf
file_size: 998706
relation: main_file
success: 1
file_date_updated: 2020-12-11T12:33:04Z
has_accepted_license: '1'
keyword:
- voice activity detection
- speech activity detection
- neural network
- statistical speech processing
language:
- iso: eng
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: INTERSPEECH 2020 Virtual Shanghai China
status: public
title: Statistical and Neural Network Based Speech Activity Detection in Non-Stationary
Acoustic Environments
type: conference
user_id: '460'
year: '2020'
...
---
_id: '45383'
author:
- first_name: Jennifer
full_name: Dröse, Jennifer
id: '85820'
last_name: Dröse
- first_name: Susanne
full_name: Prediger, Susanne
last_name: Prediger
citation:
ama: 'Dröse J, Prediger S. Enhancing Fifth Graders’ Awareness of Syntactic Features
in Mathematical Word Problems: A Design Research Study on the Variation Principle.
Journal für Mathematik-Didaktik, 41(2). Published online 2020:399-422.
doi:doi.org/10.1007/s13138-019-00153-z'
apa: 'Dröse, J., & Prediger, S. (2020). Enhancing Fifth Graders’ Awareness of
Syntactic Features in Mathematical Word Problems: A Design Research Study on the
Variation Principle. Journal Für Mathematik-Didaktik, 41(2), 399–422. https://doi.org/doi.org/10.1007/s13138-019-00153-z'
bibtex: '@article{Dröse_Prediger_2020, title={Enhancing Fifth Graders’ Awareness
of Syntactic Features in Mathematical Word Problems: A Design Research Study on
the Variation Principle}, DOI={doi.org/10.1007/s13138-019-00153-z},
journal={Journal für Mathematik-Didaktik, 41(2)}, author={Dröse, Jennifer and
Prediger, Susanne}, year={2020}, pages={399–422} }'
chicago: 'Dröse, Jennifer, and Susanne Prediger. “Enhancing Fifth Graders’ Awareness
of Syntactic Features in Mathematical Word Problems: A Design Research Study on
the Variation Principle.” Journal Für Mathematik-Didaktik, 41(2), 2020,
399–422. https://doi.org/doi.org/10.1007/s13138-019-00153-z.'
ieee: 'J. Dröse and S. Prediger, “Enhancing Fifth Graders’ Awareness of Syntactic
Features in Mathematical Word Problems: A Design Research Study on the Variation
Principle,” Journal für Mathematik-Didaktik, 41(2), pp. 399–422, 2020,
doi: doi.org/10.1007/s13138-019-00153-z.'
mla: 'Dröse, Jennifer, and Susanne Prediger. “Enhancing Fifth Graders’ Awareness
of Syntactic Features in Mathematical Word Problems: A Design Research Study on
the Variation Principle.” Journal Für Mathematik-Didaktik, 41(2), 2020,
pp. 399–422, doi:doi.org/10.1007/s13138-019-00153-z.'
short: J. Dröse, S. Prediger, Journal Für Mathematik-Didaktik, 41(2) (2020) 399–422.
date_created: 2023-05-31T07:16:27Z
date_updated: 2023-11-02T08:06:54Z
department:
- _id: '98'
doi: doi.org/10.1007/s13138-019-00153-z
language:
- iso: eng
page: 399-422
publication: Journal für Mathematik-Didaktik, 41(2)
quality_controlled: '1'
status: public
title: 'Enhancing Fifth Graders’ Awareness of Syntactic Features in Mathematical Word
Problems: A Design Research Study on the Variation Principle'
type: journal_article
user_id: '85820'
year: '2020'
...
---
_id: '29413'
author:
- first_name: K.
full_name: Flaßkamp, K.
last_name: Flaßkamp
- first_name: Sina
full_name: Ober-Blöbaum, Sina
id: '16494'
last_name: Ober-Blöbaum
- first_name: 'S. '
full_name: 'Peitz, S. '
last_name: Peitz
citation:
ama: 'Flaßkamp K, Ober-Blöbaum S, Peitz S. Symmetry in optimal control: A multiobjective
model predictive control approach. In: Junge O, Schütze O, Froyland G, Ober-Blöbaum
S, Padberg-Gehle K, eds. Advances in Dynamics, Optimization and Computation.
Springer International Publishing; 2020:209-237.'
apa: 'Flaßkamp, K., Ober-Blöbaum, S., & Peitz, S. (2020). Symmetry in optimal
control: A multiobjective model predictive control approach. In O. Junge, O. Schütze,
G. Froyland, S. Ober-Blöbaum, & K. Padberg-Gehle (Eds.), Advances in Dynamics,
Optimization and Computation (pp. 209–237). Springer International Publishing.'
bibtex: '@inbook{Flaßkamp_Ober-Blöbaum_Peitz_2020, place={Cham}, title={Symmetry
in optimal control: A multiobjective model predictive control approach}, booktitle={Advances
in Dynamics, Optimization and Computation}, publisher={Springer International
Publishing}, author={Flaßkamp, K. and Ober-Blöbaum, Sina and Peitz, S. }, editor={Junge,
Oliver and Schütze, Oliver and Froyland, Gary and Ober-Blöbaum, Sina and Padberg-Gehle,
Kathrin}, year={2020}, pages={209–237} }'
chicago: 'Flaßkamp, K., Sina Ober-Blöbaum, and S. Peitz. “Symmetry in Optimal Control:
A Multiobjective Model Predictive Control Approach.” In Advances in Dynamics,
Optimization and Computation, edited by Oliver Junge, Oliver Schütze, Gary
Froyland, Sina Ober-Blöbaum, and Kathrin Padberg-Gehle, 209–37. Cham: Springer
International Publishing, 2020.'
ieee: 'K. Flaßkamp, S. Ober-Blöbaum, and S. Peitz, “Symmetry in optimal control:
A multiobjective model predictive control approach,” in Advances in Dynamics,
Optimization and Computation, O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum,
and K. Padberg-Gehle, Eds. Cham: Springer International Publishing, 2020, pp.
209–237.'
mla: 'Flaßkamp, K., et al. “Symmetry in Optimal Control: A Multiobjective Model
Predictive Control Approach.” Advances in Dynamics, Optimization and Computation,
edited by Oliver Junge et al., Springer International Publishing, 2020, pp. 209–37.'
short: 'K. Flaßkamp, S. Ober-Blöbaum, S. Peitz, in: O. Junge, O. Schütze, G. Froyland,
S. Ober-Blöbaum, K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and
Computation, Springer International Publishing, Cham, 2020, pp. 209–237.'
date_created: 2022-01-18T12:58:18Z
date_updated: 2023-11-08T08:15:14Z
department:
- _id: '636'
editor:
- first_name: Oliver
full_name: Junge, Oliver
last_name: Junge
- first_name: Oliver
full_name: Schütze, Oliver
last_name: Schütze
- first_name: Gary
full_name: Froyland, Gary
last_name: Froyland
- first_name: Sina
full_name: Ober-Blöbaum, Sina
last_name: Ober-Blöbaum
- first_name: Kathrin
full_name: Padberg-Gehle, Kathrin
last_name: Padberg-Gehle
language:
- iso: eng
page: 209-237
place: Cham
publication: Advances in Dynamics, Optimization and Computation
publisher: Springer International Publishing
status: public
title: 'Symmetry in optimal control: A multiobjective model predictive control approach'
type: book_chapter
user_id: '15694'
year: '2020'
...
---
_id: '20762'
abstract:
- lang: eng
text: The rising interest in single-channel multi-speaker speech separation sparked
development of End-to-End (E2E) approaches to multispeaker speech recognition.
However, up until now, state-of-theart neural network–based time domain source
separation has not yet been combined with E2E speech recognition. We here demonstrate
how to combine a separation module based on a Convolutional Time domain Audio
Separation Network (Conv-TasNet) with an E2E speech recognizer and how to train
such a model jointly by distributing it over multiple GPUs or by approximating
truncated back-propagation for the convolutional front-end. To put this work into
perspective and illustrate the complexity of the design space, we provide a compact
overview of single-channel multi-speaker recognition systems. Our experiments
show a word error rate of 11.0% on WSJ0-2mix and indicate that our joint time
domain model can yield substantial improvements over cascade DNN-HMM and monolithic
E2E frequency domain systems proposed so far.
author:
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Lukas
full_name: Drude, Lukas
last_name: Drude
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Tomohiro
full_name: Nakatani, Tomohiro
last_name: Nakatani
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'von Neumann T, Kinoshita K, Drude L, et al. End-to-End Training of Time Domain
Audio Separation and Recognition. In: ICASSP 2020 - 2020 IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP). ; 2020:7004-7008.
doi:10.1109/ICASSP40776.2020.9053461'
apa: von Neumann, T., Kinoshita, K., Drude, L., Boeddeker, C., Delcroix, M., Nakatani,
T., & Haeb-Umbach, R. (2020). End-to-End Training of Time Domain Audio Separation
and Recognition. ICASSP 2020 - 2020 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP), 7004–7008. https://doi.org/10.1109/ICASSP40776.2020.9053461
bibtex: '@inproceedings{von Neumann_Kinoshita_Drude_Boeddeker_Delcroix_Nakatani_Haeb-Umbach_2020,
title={End-to-End Training of Time Domain Audio Separation and Recognition}, DOI={10.1109/ICASSP40776.2020.9053461},
booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)}, author={von Neumann, Thilo and Kinoshita, Keisuke
and Drude, Lukas and Boeddeker, Christoph and Delcroix, Marc and Nakatani, Tomohiro
and Haeb-Umbach, Reinhold}, year={2020}, pages={7004–7008} }'
chicago: Neumann, Thilo von, Keisuke Kinoshita, Lukas Drude, Christoph Boeddeker,
Marc Delcroix, Tomohiro Nakatani, and Reinhold Haeb-Umbach. “End-to-End Training
of Time Domain Audio Separation and Recognition.” In ICASSP 2020 - 2020 IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP),
7004–8, 2020. https://doi.org/10.1109/ICASSP40776.2020.9053461.
ieee: 'T. von Neumann et al., “End-to-End Training of Time Domain Audio Separation
and Recognition,” in ICASSP 2020 - 2020 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP), 2020, pp. 7004–7008, doi: 10.1109/ICASSP40776.2020.9053461.'
mla: von Neumann, Thilo, et al. “End-to-End Training of Time Domain Audio Separation
and Recognition.” ICASSP 2020 - 2020 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP), 2020, pp. 7004–08, doi:10.1109/ICASSP40776.2020.9053461.
short: 'T. von Neumann, K. Kinoshita, L. Drude, C. Boeddeker, M. Delcroix, T. Nakatani,
R. Haeb-Umbach, in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP), 2020, pp. 7004–7008.'
date_created: 2020-12-16T14:07:54Z
date_updated: 2023-11-15T12:17:45Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.1109/ICASSP40776.2020.9053461
file:
- access_level: open_access
content_type: application/pdf
creator: huesera
date_created: 2020-12-16T14:09:48Z
date_updated: 2020-12-16T14:09:48Z
file_id: '20763'
file_name: ICASSP_2020_vonNeumann_Paper.pdf
file_size: 192529
relation: main_file
file_date_updated: 2020-12-16T14:09:48Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 7004-7008
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
quality_controlled: '1'
status: public
title: End-to-End Training of Time Domain Audio Separation and Recognition
type: conference
user_id: '49870'
year: '2020'
...
---
_id: '20764'
abstract:
- lang: eng
text: 'Most approaches to multi-talker overlapped speech separation and recognition
assume that the number of simultaneously active speakers is given, but in realistic
situations, it is typically unknown. To cope with this, we extend an iterative
speech extraction system with mechanisms to count the number of sources and combine
it with a single-talker speech recognizer to form the first end-to-end multi-talker
automatic speech recognition system for an unknown number of active speakers.
Our experiments show very promising performance in counting accuracy, source separation
and speech recognition on simulated clean mixtures from WSJ0-2mix and WSJ0-3mix.
Among others, we set a new state-of-the-art word error rate on the WSJ0-2mix database.
Furthermore, our system generalizes well to a larger number of speakers than it
ever saw during training, as shown in experiments with the WSJ0-4mix database. '
author:
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Lukas
full_name: Drude, Lukas
last_name: Drude
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Tomohiro
full_name: Nakatani, Tomohiro
last_name: Nakatani
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'von Neumann T, Boeddeker C, Drude L, et al. Multi-Talker ASR for an Unknown
Number of Sources: Joint Training of Source Counting, Separation and ASR. In:
Proc. Interspeech 2020. ; 2020:3097-3101. doi:10.21437/Interspeech.2020-2519'
apa: 'von Neumann, T., Boeddeker, C., Drude, L., Kinoshita, K., Delcroix, M., Nakatani,
T., & Haeb-Umbach, R. (2020). Multi-Talker ASR for an Unknown Number of Sources:
Joint Training of Source Counting, Separation and ASR. Proc. Interspeech 2020,
3097–3101. https://doi.org/10.21437/Interspeech.2020-2519'
bibtex: '@inproceedings{von Neumann_Boeddeker_Drude_Kinoshita_Delcroix_Nakatani_Haeb-Umbach_2020,
title={Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source
Counting, Separation and ASR}, DOI={10.21437/Interspeech.2020-2519},
booktitle={Proc. Interspeech 2020}, author={von Neumann, Thilo and Boeddeker,
Christoph and Drude, Lukas and Kinoshita, Keisuke and Delcroix, Marc and Nakatani,
Tomohiro and Haeb-Umbach, Reinhold}, year={2020}, pages={3097–3101} }'
chicago: 'Neumann, Thilo von, Christoph Boeddeker, Lukas Drude, Keisuke Kinoshita,
Marc Delcroix, Tomohiro Nakatani, and Reinhold Haeb-Umbach. “Multi-Talker ASR
for an Unknown Number of Sources: Joint Training of Source Counting, Separation
and ASR.” In Proc. Interspeech 2020, 3097–3101, 2020. https://doi.org/10.21437/Interspeech.2020-2519.'
ieee: 'T. von Neumann et al., “Multi-Talker ASR for an Unknown Number of
Sources: Joint Training of Source Counting, Separation and ASR,” in Proc. Interspeech
2020, 2020, pp. 3097–3101, doi: 10.21437/Interspeech.2020-2519.'
mla: 'von Neumann, Thilo, et al. “Multi-Talker ASR for an Unknown Number of Sources:
Joint Training of Source Counting, Separation and ASR.” Proc. Interspeech 2020,
2020, pp. 3097–101, doi:10.21437/Interspeech.2020-2519.'
short: 'T. von Neumann, C. Boeddeker, L. Drude, K. Kinoshita, M. Delcroix, T. Nakatani,
R. Haeb-Umbach, in: Proc. Interspeech 2020, 2020, pp. 3097–3101.'
date_created: 2020-12-16T14:12:45Z
date_updated: 2023-11-15T12:17:57Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.21437/Interspeech.2020-2519
file:
- access_level: open_access
content_type: application/pdf
creator: huesera
date_created: 2020-12-16T14:14:14Z
date_updated: 2020-12-16T14:14:14Z
file_id: '20765'
file_name: INTERSPEECH_2020_vonNeumann_Paper.pdf
file_size: 267893
relation: main_file
file_date_updated: 2020-12-16T14:14:14Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 3097-3101
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proc. Interspeech 2020
quality_controlled: '1'
status: public
title: 'Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source
Counting, Separation and ASR'
type: conference
user_id: '49870'
year: '2020'
...
---
_id: '18651'
abstract:
- lang: eng
text: 'We present an approach to deep neural network based (DNN-based) distance
estimation in reverberant rooms for supporting geometry calibration tasks in wireless
acoustic sensor networks. Signal diffuseness information from acoustic signals
is aggregated via the coherent-to-diffuse power ratio to obtain a distance-related
feature, which is mapped to a source-to-microphone distance estimate by means
of a DNN. This information is then combined with direction-of-arrival estimates
from compact microphone arrays to infer the geometry of the sensor network. Unlike
many other approaches to geometry calibration, the proposed scheme does only require
that the sampling clocks of the sensor nodes are roughly synchronized. In simulations
we show that the proposed DNN-based distance estimator generalizes to unseen acoustic
environments and that precise estimates of the sensor node positions are obtained. '
author:
- first_name: Tobias
full_name: Gburrek, Tobias
id: '44006'
last_name: Gburrek
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Andreas
full_name: Brendel, Andreas
last_name: Brendel
- first_name: Walter
full_name: Kellermann, Walter
last_name: Kellermann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Gburrek T, Schmalenstroeer J, Brendel A, Kellermann W, Haeb-Umbach R. Deep
Neural Network based Distance Estimation for Geometry Calibration in Acoustic
Sensor Network. In: European Signal Processing Conference (EUSIPCO). ;
2020.'
apa: Gburrek, T., Schmalenstroeer, J., Brendel, A., Kellermann, W., & Haeb-Umbach,
R. (2020). Deep Neural Network based Distance Estimation for Geometry Calibration
in Acoustic Sensor Network. European Signal Processing Conference (EUSIPCO).
bibtex: '@inproceedings{Gburrek_Schmalenstroeer_Brendel_Kellermann_Haeb-Umbach_2020,
title={Deep Neural Network based Distance Estimation for Geometry Calibration
in Acoustic Sensor Network}, booktitle={European Signal Processing Conference
(EUSIPCO)}, author={Gburrek, Tobias and Schmalenstroeer, Joerg and Brendel, Andreas
and Kellermann, Walter and Haeb-Umbach, Reinhold}, year={2020} }'
chicago: Gburrek, Tobias, Joerg Schmalenstroeer, Andreas Brendel, Walter Kellermann,
and Reinhold Haeb-Umbach. “Deep Neural Network Based Distance Estimation for Geometry
Calibration in Acoustic Sensor Network.” In European Signal Processing Conference
(EUSIPCO), 2020.
ieee: T. Gburrek, J. Schmalenstroeer, A. Brendel, W. Kellermann, and R. Haeb-Umbach,
“Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic
Sensor Network,” 2020.
mla: Gburrek, Tobias, et al. “Deep Neural Network Based Distance Estimation for
Geometry Calibration in Acoustic Sensor Network.” European Signal Processing
Conference (EUSIPCO), 2020.
short: 'T. Gburrek, J. Schmalenstroeer, A. Brendel, W. Kellermann, R. Haeb-Umbach,
in: European Signal Processing Conference (EUSIPCO), 2020.'
date_created: 2020-08-31T07:20:57Z
date_updated: 2023-11-17T06:23:39Z
ddc:
- '004'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: tgburrek
date_created: 2023-11-17T06:21:40Z
date_updated: 2023-11-17T06:21:40Z
file_id: '48987'
file_name: Gburrek2020.pdf
file_size: 292159
relation: main_file
file_date_updated: 2023-11-17T06:21:40Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
publication: European Signal Processing Conference (EUSIPCO)
quality_controlled: '1'
status: public
title: Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic
Sensor Network
type: conference
user_id: '44006'
year: '2020'
...
---
_id: '31553'
author:
- first_name: Susanne
full_name: Seitz, Susanne
last_name: Seitz
- first_name: Uta
full_name: Häsel-Weide, Uta
id: '60267'
last_name: Häsel-Weide
- first_name: Yannik
full_name: Wilke, Yannik
last_name: Wilke
- first_name: Melina
full_name: Wallner, Melina
id: '45445'
last_name: Wallner
citation:
ama: Seitz S, Häsel-Weide U, Wilke Y, Wallner M. Expertise von Lehrpersonen für
inklusiven Mathematikunterricht der Sekundarstufe - Ausgangspunkte zur Professionalisierungsforschung.
K:ON Kölner Online-Journal für Lehrer*innenbildung. 2020;(2). doi:10.18716/ojs/kON/2020.2.03
apa: Seitz, S., Häsel-Weide, U., Wilke, Y., & Wallner, M. (2020). Expertise
von Lehrpersonen für inklusiven Mathematikunterricht der Sekundarstufe - Ausgangspunkte
zur Professionalisierungsforschung. K:ON Kölner Online-Journal für Lehrer*innenbildung,
2. https://doi.org/10.18716/ojs/kON/2020.2.03
bibtex: '@article{Seitz_Häsel-Weide_Wilke_Wallner_2020, title={Expertise von Lehrpersonen
für inklusiven Mathematikunterricht der Sekundarstufe - Ausgangspunkte zur Professionalisierungsforschung.},
DOI={10.18716/ojs/kON/2020.2.03},
number={2}, journal={K:ON Kölner Online-Journal für Lehrer*innenbildung}, author={Seitz,
Susanne and Häsel-Weide, Uta and Wilke, Yannik and Wallner, Melina}, year={2020}
}'
chicago: Seitz, Susanne, Uta Häsel-Weide, Yannik Wilke, and Melina Wallner. “Expertise
von Lehrpersonen für inklusiven Mathematikunterricht der Sekundarstufe - Ausgangspunkte
zur Professionalisierungsforschung.” K:ON Kölner Online-Journal für Lehrer*innenbildung,
no. 2 (2020). https://doi.org/10.18716/ojs/kON/2020.2.03.
ieee: 'S. Seitz, U. Häsel-Weide, Y. Wilke, and M. Wallner, “Expertise von Lehrpersonen
für inklusiven Mathematikunterricht der Sekundarstufe - Ausgangspunkte zur Professionalisierungsforschung.,”
K:ON Kölner Online-Journal für Lehrer*innenbildung, no. 2, 2020, doi: 10.18716/ojs/kON/2020.2.03.'
mla: Seitz, Susanne, et al. “Expertise von Lehrpersonen für inklusiven Mathematikunterricht
der Sekundarstufe - Ausgangspunkte zur Professionalisierungsforschung.” K:ON
Kölner Online-Journal für Lehrer*innenbildung, no. 2, 2020, doi:10.18716/ojs/kON/2020.2.03.
short: S. Seitz, U. Häsel-Weide, Y. Wilke, M. Wallner, K:ON Kölner Online-Journal
für Lehrer*innenbildung (2020).
date_created: 2022-05-31T08:11:34Z
date_updated: 2023-11-24T16:50:38Z
department:
- _id: '98'
- _id: '543'
doi: 10.18716/ojs/kON/2020.2.03
issue: '2'
language:
- iso: ger
publication: K:ON Kölner Online-Journal für Lehrer*innenbildung
publication_status: published
status: public
title: Expertise von Lehrpersonen für inklusiven Mathematikunterricht der Sekundarstufe
- Ausgangspunkte zur Professionalisierungsforschung.
type: journal_article
user_id: '45445'
year: '2020'
...
---
_id: '46328'
abstract:
- lang: eng
text: In this paper, we rely on previous work proposing a modularized version of
CMA-ES, which captures several alterations to the conventional CMA-ES developed
in recent years. Each alteration provides significant advantages under certain
problem properties, e.g., multi-modality, high conditioning. These distinct advancements
are implemented as modules which result in 4608 unique versions of CMA-ES. Previous
findings illustrate the competitive advantage of enabling and disabling the aforementioned
modules for different optimization problems. Yet, this modular CMA-ES is lacking
a method to automatically determine when the activation of specific modules is
auspicious and when it is not. We propose a well-performing instance-specific
algorithm configuration model which selects an (almost) optimal configuration
of modules for a given problem instance. In addition, the structure of this configuration
model is able to capture inter-dependencies between modules, e.g., two (or more)
modules might only be advantageous in unison for some problem types, making the
orchestration of modules a crucial task. This is accomplished by chaining multiple
random forest classifiers together into a so-called Classifier Chain based on
a set of numerical features extracted by means of Exploratory Landscape Analysis
(ELA) to describe the given problem instances.
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Hao
full_name: Wang, Hao
last_name: Wang
- first_name: Thomas H. W.
full_name: Bäck, Thomas H. W.
last_name: Bäck
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
citation:
ama: 'Prager RP, Trautmann H, Wang H, Bäck THW, Kerschke P. Per-Instance Configuration
of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape
Analysis. In: Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI). ; 2020:996–1003. doi:10.1109/SSCI47803.2020.9308510'
apa: Prager, R. P., Trautmann, H., Wang, H., Bäck, T. H. W., & Kerschke, P.
(2020). Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier
Chains and Exploratory Landscape Analysis. Proceedings of the IEEE Symposium
Series on Computational Intelligence (SSCI), 996–1003. https://doi.org/10.1109/SSCI47803.2020.9308510
bibtex: '@inproceedings{Prager_Trautmann_Wang_Bäck_Kerschke_2020, place={Canberra,
Australia}, title={Per-Instance Configuration of the Modularized CMA-ES by Means
of Classifier Chains and Exploratory Landscape Analysis}, DOI={10.1109/SSCI47803.2020.9308510},
booktitle={Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI)}, author={Prager, Raphael Patrick and Trautmann, Heike and Wang, Hao and
Bäck, Thomas H. W. and Kerschke, Pascal}, year={2020}, pages={996–1003} }'
chicago: Prager, Raphael Patrick, Heike Trautmann, Hao Wang, Thomas H. W. Bäck,
and Pascal Kerschke. “Per-Instance Configuration of the Modularized CMA-ES by
Means of Classifier Chains and Exploratory Landscape Analysis.” In Proceedings
of the IEEE Symposium Series on Computational Intelligence (SSCI), 996–1003.
Canberra, Australia, 2020. https://doi.org/10.1109/SSCI47803.2020.9308510.
ieee: 'R. P. Prager, H. Trautmann, H. Wang, T. H. W. Bäck, and P. Kerschke, “Per-Instance
Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory
Landscape Analysis,” in Proceedings of the IEEE Symposium Series on Computational
Intelligence (SSCI), 2020, pp. 996–1003, doi: 10.1109/SSCI47803.2020.9308510.'
mla: Prager, Raphael Patrick, et al. “Per-Instance Configuration of the Modularized
CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis.” Proceedings
of the IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp.
996–1003, doi:10.1109/SSCI47803.2020.9308510.
short: 'R.P. Prager, H. Trautmann, H. Wang, T.H.W. Bäck, P. Kerschke, in: Proceedings
of the IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia,
2020, pp. 996–1003.'
date_created: 2023-08-04T07:37:30Z
date_updated: 2023-10-16T13:04:15Z
department:
- _id: '34'
- _id: '819'
doi: 10.1109/SSCI47803.2020.9308510
language:
- iso: eng
page: 996–1003
place: Canberra, Australia
publication: Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI)
status: public
title: Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier
Chains and Exploratory Landscape Analysis
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46320'
abstract:
- lang: eng
text: The identification of coordinated campaigns within Social Media is a complex
task that is often hindered by missing labels and large amounts of data that have
to be processed. We propose a new two-phase framework that uses unsupervised stream
clustering for detecting suspicious trends over time in a first step. Afterwards,
traditional offline analyses are applied to distinguish between normal trend evolution
and malicious manipulation attempts. We demonstrate the applicability of our framework
in the context of the final days of the Brexit in 2019/2020.
author:
- first_name: D
full_name: Assenmacher, D
last_name: Assenmacher
- first_name: L
full_name: Clever, L
last_name: Clever
- first_name: JS
full_name: Pohl, JS
last_name: Pohl
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: C
full_name: Grimme, C
last_name: Grimme
citation:
ama: 'Assenmacher D, Clever L, Pohl J, Trautmann H, Grimme C. A Two-Phase Framework
for Detecting Manipulation Campaigns in Social Media. In: Meiselwitz G, ed. Proceedings
of the International Conference on Human-Computer Interaction (HCII 2020): Social
Computing and Social Media. Design, Ethics, User Behavior, and Social Network
Analysis. Springer International Publishing; 2020:201–214. doi:10.1007/978-3-030-49570-1_14'
apa: 'Assenmacher, D., Clever, L., Pohl, J., Trautmann, H., & Grimme, C. (2020).
A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. In
G. Meiselwitz (Ed.), Proceedings of the International Conference on Human-Computer
Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User
Behavior, and Social Network Analysis (pp. 201–214). Springer International
Publishing. https://doi.org/10.1007/978-3-030-49570-1_14'
bibtex: '@inproceedings{Assenmacher_Clever_Pohl_Trautmann_Grimme_2020, place={Cham},
title={A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media},
DOI={10.1007/978-3-030-49570-1_14},
booktitle={Proceedings of the International Conference on Human-Computer Interaction
(HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior,
and Social Network Analysis}, publisher={Springer International Publishing}, author={Assenmacher,
D and Clever, L and Pohl, JS and Trautmann, Heike and Grimme, C}, editor={Meiselwitz,
G}, year={2020}, pages={201–214} }'
chicago: 'Assenmacher, D, L Clever, JS Pohl, Heike Trautmann, and C Grimme. “A Two-Phase
Framework for Detecting Manipulation Campaigns in Social Media.” In Proceedings
of the International Conference on Human-Computer Interaction (HCII 2020): Social
Computing and Social Media. Design, Ethics, User Behavior, and Social Network
Analysis, edited by G Meiselwitz, 201–214. Cham: Springer International Publishing,
2020. https://doi.org/10.1007/978-3-030-49570-1_14.'
ieee: 'D. Assenmacher, L. Clever, J. Pohl, H. Trautmann, and C. Grimme, “A Two-Phase
Framework for Detecting Manipulation Campaigns in Social Media,” in Proceedings
of the International Conference on Human-Computer Interaction (HCII 2020): Social
Computing and Social Media. Design, Ethics, User Behavior, and Social Network
Analysis, 2020, pp. 201–214, doi: 10.1007/978-3-030-49570-1_14.'
mla: 'Assenmacher, D., et al. “A Two-Phase Framework for Detecting Manipulation
Campaigns in Social Media.” Proceedings of the International Conference on
Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design,
Ethics, User Behavior, and Social Network Analysis, edited by G Meiselwitz,
Springer International Publishing, 2020, pp. 201–214, doi:10.1007/978-3-030-49570-1_14.'
short: 'D. Assenmacher, L. Clever, J. Pohl, H. Trautmann, C. Grimme, in: G. Meiselwitz
(Ed.), Proceedings of the International Conference on Human-Computer Interaction
(HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior,
and Social Network Analysis, Springer International Publishing, Cham, 2020, pp.
201–214.'
date_created: 2023-08-04T07:30:29Z
date_updated: 2023-10-16T12:59:28Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-030-49570-1_14
editor:
- first_name: G
full_name: Meiselwitz, G
last_name: Meiselwitz
language:
- iso: eng
page: 201–214
place: Cham
publication: 'Proceedings of the International Conference on Human-Computer Interaction
(HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and
Social Network Analysis'
publication_identifier:
isbn:
- 978-3-030-49570-1
publisher: Springer International Publishing
status: public
title: A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46325'
abstract:
- lang: eng
text: Clustering is an important technique in data analysis which can reveal hidden
patterns and unknown relationships in the data. A common problem in clustering
is the proper choice of parameter settings. To tackle this, automated algorithm
configuration is available which can automatically find the best parameter settings.
In practice, however, many of our today’s data sources are data streams due to
the widespread deployment of sensors, the internet-of-things or (social) media.
Stream clustering aims to tackle this challenge by identifying, tracking and updating
clusters over time. Unfortunately, none of the existing approaches for automated
algorithm configuration are directly applicable to the streaming scenario. In
this paper, we explore the possibility of automated algorithm configuration for
stream clustering algorithms using an ensemble of different configurations. In
first experiments, we demonstrate that our approach is able to automatically find
superior configurations and refine them over time.
author:
- first_name: Matthias
full_name: Carnein, Matthias
last_name: Carnein
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Albert
full_name: Bifet, Albert
last_name: Bifet
- first_name: Bernhard
full_name: Pfahringer, Bernhard
last_name: Pfahringer
citation:
ama: 'Carnein M, Trautmann H, Bifet A, Pfahringer B. Towards Automated Configuration
of Stream Clustering Algorithms. In: Proceedings of the European Conference
on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
(ECMLPKDD ’19). ; 2020:137–143. doi:10.1007/978-3-030-43823-4_12'
apa: Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2020). Towards
Automated Configuration of Stream Clustering Algorithms. Proceedings of the
European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECMLPKDD ’19), 137–143. https://doi.org/10.1007/978-3-030-43823-4_12
bibtex: '@inproceedings{Carnein_Trautmann_Bifet_Pfahringer_2020, place={Würzburg,
Germany}, title={Towards Automated Configuration of Stream Clustering Algorithms},
DOI={10.1007/978-3-030-43823-4_12},
booktitle={Proceedings of the European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19)}, author={Carnein,
Matthias and Trautmann, Heike and Bifet, Albert and Pfahringer, Bernhard}, year={2020},
pages={137–143} }'
chicago: Carnein, Matthias, Heike Trautmann, Albert Bifet, and Bernhard Pfahringer.
“Towards Automated Configuration of Stream Clustering Algorithms.” In Proceedings
of the European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECMLPKDD ’19), 137–143. Würzburg, Germany,
2020. https://doi.org/10.1007/978-3-030-43823-4_12.
ieee: 'M. Carnein, H. Trautmann, A. Bifet, and B. Pfahringer, “Towards Automated
Configuration of Stream Clustering Algorithms,” in Proceedings of the European
Conference on Machine Learning and Principles and Practice of Knowledge Discovery
in Databases (ECMLPKDD ’19), 2020, pp. 137–143, doi: 10.1007/978-3-030-43823-4_12.'
mla: Carnein, Matthias, et al. “Towards Automated Configuration of Stream Clustering
Algorithms.” Proceedings of the European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19),
2020, pp. 137–143, doi:10.1007/978-3-030-43823-4_12.
short: 'M. Carnein, H. Trautmann, A. Bifet, B. Pfahringer, in: Proceedings of the
European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECMLPKDD ’19), Würzburg, Germany, 2020, pp. 137–143.'
date_created: 2023-08-04T07:35:24Z
date_updated: 2023-10-16T13:03:15Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-030-43823-4_12
language:
- iso: eng
page: 137–143
place: Würzburg, Germany
publication: Proceedings of the European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases (ECMLPKDD ’19)
publication_identifier:
isbn:
- 978-3-030-43823-4
status: public
title: Towards Automated Configuration of Stream Clustering Algorithms
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46321'
abstract:
- lang: eng
text: Social bots have recently gained attention in the context of public opinion
manipulation on social media platforms. While a lot of research effort has been
put into the classification and detection of such automated programs, it is still
unclear how technically sophisticated those bots are, which platforms they target,
and where they originate from. To answer these questions, we gathered repository
data from open source collaboration platforms to identify the status-quo of social
bot development as well as first insights into the overall skills of publicly
available bot code.
author:
- first_name: Dennis
full_name: Assenmacher, Dennis
last_name: Assenmacher
- first_name: Lena
full_name: Frischlich , Lena
last_name: 'Frischlich '
- 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
- first_name: Lena
full_name: Adam, Lena
last_name: Adam
citation:
ama: 'Assenmacher D, Frischlich L, Trautmann H, Grimme C, Adam L. Inside the tool
set of automation: Free social bot code revisited. In: Grimme C, Preuß M, Takes
F, Waldherr A, eds. Disinformation in Open Online Media. Lecture Notes
in Computer Science. Springer; 2020:101–114.'
apa: 'Assenmacher, D., Frischlich , L., Trautmann, H., Grimme, C., & Adam, L.
(2020). Inside the tool set of automation: Free social bot code revisited. In
C. Grimme, M. Preuß, F. Takes, & A. Waldherr (Eds.), Disinformation in
open online media (pp. 101–114). Springer.'
bibtex: '@inproceedings{Assenmacher_Frischlich _Trautmann_Grimme_Adam_2020, place={Wiesbaden},
series={Lecture Notes in Computer Science}, title={Inside the tool set of automation:
Free social bot code revisited}, booktitle={Disinformation in open online media},
publisher={Springer}, author={Assenmacher, Dennis and Frischlich , Lena and Trautmann,
Heike and Grimme, Christian and Adam, Lena}, editor={Grimme, Christian and Preuß,
Mike and Takes, Frank and Waldherr, Annie}, year={2020}, pages={101–114}, collection={Lecture
Notes in Computer Science} }'
chicago: 'Assenmacher, Dennis, Lena Frischlich , Heike Trautmann, Christian Grimme,
and Lena Adam. “Inside the Tool Set of Automation: Free Social Bot Code Revisited.”
In Disinformation in Open Online Media, edited by Christian Grimme, Mike
Preuß, Frank Takes, and Annie Waldherr, 101–114. Lecture Notes in Computer Science.
Wiesbaden: Springer, 2020.'
ieee: 'D. Assenmacher, L. Frischlich , H. Trautmann, C. Grimme, and L. Adam, “Inside
the tool set of automation: Free social bot code revisited,” in Disinformation
in open online media, 2020, pp. 101–114.'
mla: 'Assenmacher, Dennis, et al. “Inside the Tool Set of Automation: Free Social
Bot Code Revisited.” Disinformation in Open Online Media, edited by Christian
Grimme et al., Springer, 2020, pp. 101–114.'
short: 'D. Assenmacher, L. Frischlich , H. Trautmann, C. Grimme, L. Adam, in: C.
Grimme, M. Preuß, F. Takes, A. Waldherr (Eds.), Disinformation in Open Online
Media, Springer, Wiesbaden, 2020, pp. 101–114.'
date_created: 2023-08-04T07:31:13Z
date_updated: 2023-10-16T13:00:15Z
department:
- _id: '34'
- _id: '819'
editor:
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Mike
full_name: Preuß, Mike
last_name: Preuß
- first_name: Frank
full_name: Takes, Frank
last_name: Takes
- first_name: Annie
full_name: Waldherr, Annie
last_name: Waldherr
language:
- iso: eng
page: 101–114
place: Wiesbaden
publication: Disinformation in open online media
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: 'Inside the tool set of automation: Free social bot code revisited'
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46326'
abstract:
- lang: eng
text: Machine learning has become one of the most important tools in data analysis.
However, selecting the most appropriate machine learning algorithm and tuning
its hyperparameters to their optimal values remains a difficult task. This is
even more difficult for streaming applications where automated approaches are
often not available to help during algorithm selection and configuration. This
paper proposes the first approach for automated algorithm selection and configuration
of stream clustering algorithms. We train an ensemble of different stream clustering
algorithms and configurations in parallel and use the best performing configuration
to obtain a clustering solution. By drawing new configurations from better performing
ones, we are able to improve the ensemble performance over time. In large experiments
on real and artificial data we show how our ensemble approach can improve upon
default configurations and can also compete with a-posteriori algorithm configuration.
Our approach is considerably faster than a-posteriori approaches and applicable
in real-time. In addition, it is not limited to stream clustering and can be generalised
to all streaming applications, including stream classification and regression.
author:
- first_name: Matthias
full_name: Carnein, Matthias
last_name: Carnein
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Albert
full_name: Bifet, Albert
last_name: Bifet
- first_name: Bernhard
full_name: Pfahringer, Bernhard
last_name: Pfahringer
citation:
ama: 'Carnein M, Trautmann H, Bifet A, Pfahringer B. confStream: Automated Algorithm
Selection and Configuration of Stream Clustering Algorithms. In: Proceedings
of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020).
; 2020:80–95. doi:10.1007/978-3-030-53552-0_10'
apa: 'Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2020). confStream:
Automated Algorithm Selection and Configuration of Stream Clustering Algorithms.
Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference
(LION 2020), 80–95. https://doi.org/10.1007/978-3-030-53552-0_10'
bibtex: '@inproceedings{Carnein_Trautmann_Bifet_Pfahringer_2020, place={Athens,
Greece}, title={confStream: Automated Algorithm Selection and Configuration of
Stream Clustering Algorithms}, DOI={10.1007/978-3-030-53552-0_10},
booktitle={Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference
(LION 2020)}, author={Carnein, Matthias and Trautmann, Heike and Bifet, Albert
and Pfahringer, Bernhard}, year={2020}, pages={80–95} }'
chicago: 'Carnein, Matthias, Heike Trautmann, Albert Bifet, and Bernhard Pfahringer.
“ConfStream: Automated Algorithm Selection and Configuration of Stream Clustering
Algorithms.” In Proceedings of the 14$^th$ Learning and Intelligent Optimization
Conference (LION 2020), 80–95. Athens, Greece, 2020. https://doi.org/10.1007/978-3-030-53552-0_10.'
ieee: 'M. Carnein, H. Trautmann, A. Bifet, and B. Pfahringer, “confStream: Automated
Algorithm Selection and Configuration of Stream Clustering Algorithms,” in Proceedings
of the 14$^th$ Learning and Intelligent Optimization Conference (LION 2020),
2020, pp. 80–95, doi: 10.1007/978-3-030-53552-0_10.'
mla: 'Carnein, Matthias, et al. “ConfStream: Automated Algorithm Selection and Configuration
of Stream Clustering Algorithms.” Proceedings of the 14$^th$ Learning and Intelligent
Optimization Conference (LION 2020), 2020, pp. 80–95, doi:10.1007/978-3-030-53552-0_10.'
short: 'M. Carnein, H. Trautmann, A. Bifet, B. Pfahringer, in: Proceedings of the
14$^th$ Learning and Intelligent Optimization Conference (LION 2020), Athens,
Greece, 2020, pp. 80–95.'
date_created: 2023-08-04T07:36:03Z
date_updated: 2023-10-16T13:03:36Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-030-53552-0_10
language:
- iso: eng
page: 80–95
place: Athens, Greece
publication: Proceedings of the 14$^th$ Learning and Intelligent Optimization Conference
(LION 2020)
status: public
title: 'confStream: Automated Algorithm Selection and Configuration of Stream Clustering
Algorithms'
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46327'
abstract:
- lang: eng
text: In online media environments, nostalgia can be used as important ingredient
of propaganda strategies, specifically, by creating societal pessimism. This work
addresses the automated detection of nostalgic text as a first step towards automatically
identifying nostalgia-based manipulation strategies. We compare the performance
of standard machine learning approaches on this challenge and demonstrate the
successful transfer of the best performing approach to real-world nostalgia detection
in a case study.
author:
- first_name: Clever
full_name: Lena, Clever
last_name: Lena
- first_name: Lena
full_name: Frischlich, Lena
last_name: Frischlich
- 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: 'Lena C, Frischlich L, Trautmann H, Grimme C. Automated detection of nostalgic
text in the context of societal pessimism. In: Grimme C, Preuß M, Takes F, Waldherr
A, eds. Disinformation in Open Online Media. ; 2020:48–58.'
apa: Lena, C., Frischlich, L., Trautmann, H., & Grimme, C. (2020). Automated
detection of nostalgic text in the context of societal pessimism. In C. Grimme,
M. Preuß, F. Takes, & A. Waldherr (Eds.), Disinformation in open online
media (pp. 48–58).
bibtex: '@inproceedings{Lena_Frischlich_Trautmann_Grimme_2020, place={Hamburg, Deutschland},
title={Automated detection of nostalgic text in the context of societal pessimism},
booktitle={Disinformation in open online media}, author={Lena, Clever and Frischlich,
Lena and Trautmann, Heike and Grimme, Christian}, editor={Grimme, Christian and
Preuß, Mike and Takes, Frank and Waldherr, Annie}, year={2020}, pages={48–58}
}'
chicago: Lena, Clever, Lena Frischlich, Heike Trautmann, and Christian Grimme. “Automated
Detection of Nostalgic Text in the Context of Societal Pessimism.” In Disinformation
in Open Online Media, edited by Christian Grimme, Mike Preuß, Frank Takes,
and Annie Waldherr, 48–58. Hamburg, Deutschland, 2020.
ieee: C. Lena, L. Frischlich, H. Trautmann, and C. Grimme, “Automated detection
of nostalgic text in the context of societal pessimism,” in Disinformation
in open online media, 2020, pp. 48–58.
mla: Lena, Clever, et al. “Automated Detection of Nostalgic Text in the Context
of Societal Pessimism.” Disinformation in Open Online Media, edited by
Christian Grimme et al., 2020, pp. 48–58.
short: 'C. Lena, L. Frischlich, H. Trautmann, C. Grimme, in: C. Grimme, M. Preuß,
F. Takes, A. Waldherr (Eds.), Disinformation in Open Online Media, Hamburg, Deutschland,
2020, pp. 48–58.'
date_created: 2023-08-04T07:36:43Z
date_updated: 2023-10-16T13:03:56Z
department:
- _id: '34'
- _id: '819'
editor:
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Mike
full_name: Preuß, Mike
last_name: Preuß
- first_name: Frank
full_name: Takes, Frank
last_name: Takes
- first_name: Annie
full_name: Waldherr, Annie
last_name: Waldherr
language:
- iso: eng
page: 48–58
place: Hamburg, Deutschland
publication: Disinformation in open online media
status: public
title: Automated detection of nostalgic text in the context of societal pessimism
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46329'
abstract:
- lang: eng
text: The past decade has been characterized by a strong increase in the use of
social media and a continuous growth of public online discussion. With the failure
of purely manual moderation, platform operators started searching for semi-automated
solutions, where the application of Natural Language Processing (NLP) and Machine
Learning (ML) techniques is promising. However, this requires huge financial investments
for algorithmic implementations, data collection, and model training, which only
big players can afford. To support smaller or medium-sized media enterprises (SME),
we developed an integrated comment moderation system as an IT platform. This platform
acts as a service provider and offers Analytics as a Service (AaaS) to SMEs. Operating
such a platform, however, requires a robust technology stack, integrated workflows
and well-defined interfaces between all parties. In this paper, we develop and
discuss a suitable IT architecture and present a prototypical implementation.
author:
- first_name: Dennis M.
full_name: Riehle, Dennis M.
last_name: Riehle
- first_name: Marco
full_name: Niemann, Marco
last_name: Niemann
- first_name: Jens
full_name: Brunk, Jens
last_name: Brunk
- first_name: Dennis
full_name: Assenmacher, Dennis
last_name: Assenmacher
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Jörg
full_name: Becker, Jörg
last_name: Becker
citation:
ama: 'Riehle DM, Niemann M, Brunk J, Assenmacher D, Trautmann H, Becker J. Building
an Integrated Comment Moderation System – Towards a Semi-automatic Moderation
Tool. In: Meiselwitz G, ed. Social Computing and Social Media. Participation,
User Experience, Consumer Experience, and Applications of Social Computing.
Springer International Publishing; 2020:71–86.'
apa: Riehle, D. M., Niemann, M., Brunk, J., Assenmacher, D., Trautmann, H., &
Becker, J. (2020). Building an Integrated Comment Moderation System – Towards
a Semi-automatic Moderation Tool. In G. Meiselwitz (Ed.), Social Computing
and Social Media. Participation, User Experience, Consumer Experience, and Applications
of Social Computing (pp. 71–86). Springer International Publishing.
bibtex: '@inproceedings{Riehle_Niemann_Brunk_Assenmacher_Trautmann_Becker_2020,
place={Cham}, title={Building an Integrated Comment Moderation System – Towards
a Semi-automatic Moderation Tool}, booktitle={Social Computing and Social Media.
Participation, User Experience, Consumer Experience, and Applications of Social
Computing}, publisher={Springer International Publishing}, author={Riehle, Dennis
M. and Niemann, Marco and Brunk, Jens and Assenmacher, Dennis and Trautmann, Heike
and Becker, Jörg}, editor={Meiselwitz, Gabriele}, year={2020}, pages={71–86} }'
chicago: 'Riehle, Dennis M., Marco Niemann, Jens Brunk, Dennis Assenmacher, Heike
Trautmann, and Jörg Becker. “Building an Integrated Comment Moderation System
– Towards a Semi-Automatic Moderation Tool.” In Social Computing and Social
Media. Participation, User Experience, Consumer Experience, and Applications of
Social Computing, edited by Gabriele Meiselwitz, 71–86. Cham: Springer International
Publishing, 2020.'
ieee: D. M. Riehle, M. Niemann, J. Brunk, D. Assenmacher, H. Trautmann, and J. Becker,
“Building an Integrated Comment Moderation System – Towards a Semi-automatic Moderation
Tool,” in Social Computing and Social Media. Participation, User Experience,
Consumer Experience, and Applications of Social Computing, 2020, pp. 71–86.
mla: Riehle, Dennis M., et al. “Building an Integrated Comment Moderation System
– Towards a Semi-Automatic Moderation Tool.” Social Computing and Social Media.
Participation, User Experience, Consumer Experience, and Applications of Social
Computing, edited by Gabriele Meiselwitz, Springer International Publishing,
2020, pp. 71–86.
short: 'D.M. Riehle, M. Niemann, J. Brunk, D. Assenmacher, H. Trautmann, J. Becker,
in: G. Meiselwitz (Ed.), Social Computing and Social Media. Participation, User
Experience, Consumer Experience, and Applications of Social Computing, Springer
International Publishing, Cham, 2020, pp. 71–86.'
date_created: 2023-08-04T07:38:42Z
date_updated: 2023-10-16T13:04:36Z
department:
- _id: '34'
- _id: '819'
editor:
- first_name: Gabriele
full_name: Meiselwitz, Gabriele
last_name: Meiselwitz
language:
- iso: eng
page: 71–86
place: Cham
publication: Social Computing and Social Media. Participation, User Experience, Consumer
Experience, and Applications of Social Computing
publication_identifier:
isbn:
- 978-3-030-49576-3
publisher: Springer International Publishing
status: public
title: Building an Integrated Comment Moderation System – Towards a Semi-automatic
Moderation Tool
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '46333'
abstract:
- lang: eng
text: ' Recently, social bots, (semi-) automatized accounts in social media, gained
global attention in the context of public opinion manipulation. Dystopian scenarios
like the malicious amplification of topics, the spreading of disinformation, and
the manipulation of elections through “opinion machines” created headlines around
the globe. As a consequence, much research effort has been put into the classification
and detection of social bots. Yet, it is still unclear how easy an average online
media user can purchase social bots, which platforms they target, where they originate
from, and how sophisticated these bots are. This work provides a much needed new
perspective on these questions. By providing insights into the markets of social
bots in the clearnet and darknet as well as an exhaustive analysis of freely available
software tools for automation during the last decade, we shed light on the availability
and capabilities of automated profiles in social media platforms. Our results
confirm the increasing importance of social bot technology but also uncover an
as yet unknown discrepancy of theoretical and practically achieved artificial
intelligence in social bots: while literature reports on a high degree of intelligence
for chat bots and assumes the same for social bots, the observed degree of intelligence
in social bot implementations is limited. In fact, the overwhelming majority of
available services and software are of supportive nature and merely provide modules
of automation instead of fully fledged “intelligent” social bots. '
author:
- first_name: Dennis
full_name: Assenmacher, Dennis
last_name: Assenmacher
- first_name: Lena
full_name: Clever, Lena
last_name: Clever
- first_name: Lena
full_name: Frischlich, Lena
last_name: Frischlich
- first_name: Thorsten
full_name: Quandt, Thorsten
last_name: Quandt
- 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: 'Assenmacher D, Clever L, Frischlich L, Quandt T, Trautmann H, Grimme C. Demystifying
Social Bots: On the Intelligence of Automated Social Media Actors. Social Media
+ Society. 2020;6(3):2056305120939264. doi:10.1177/2056305120939264'
apa: 'Assenmacher, D., Clever, L., Frischlich, L., Quandt, T., Trautmann, H., &
Grimme, C. (2020). Demystifying Social Bots: On the Intelligence of Automated
Social Media Actors. Social Media + Society, 6(3), 2056305120939264.
https://doi.org/10.1177/2056305120939264'
bibtex: '@article{Assenmacher_Clever_Frischlich_Quandt_Trautmann_Grimme_2020, title={Demystifying
Social Bots: On the Intelligence of Automated Social Media Actors}, volume={6},
DOI={10.1177/2056305120939264},
number={3}, journal={Social Media + Society}, author={Assenmacher, Dennis and
Clever, Lena and Frischlich, Lena and Quandt, Thorsten and Trautmann, Heike and
Grimme, Christian}, year={2020}, pages={2056305120939264} }'
chicago: 'Assenmacher, Dennis, Lena Clever, Lena Frischlich, Thorsten Quandt, Heike
Trautmann, and Christian Grimme. “Demystifying Social Bots: On the Intelligence
of Automated Social Media Actors.” Social Media + Society 6, no. 3 (2020):
2056305120939264. https://doi.org/10.1177/2056305120939264.'
ieee: 'D. Assenmacher, L. Clever, L. Frischlich, T. Quandt, H. Trautmann, and C.
Grimme, “Demystifying Social Bots: On the Intelligence of Automated Social Media
Actors,” Social Media + Society, vol. 6, no. 3, p. 2056305120939264, 2020,
doi: 10.1177/2056305120939264.'
mla: 'Assenmacher, Dennis, et al. “Demystifying Social Bots: On the Intelligence
of Automated Social Media Actors.” Social Media + Society, vol. 6, no.
3, 2020, p. 2056305120939264, doi:10.1177/2056305120939264.'
short: D. Assenmacher, L. Clever, L. Frischlich, T. Quandt, H. Trautmann, C. Grimme,
Social Media + Society 6 (2020) 2056305120939264.
date_created: 2023-08-04T07:41:37Z
date_updated: 2023-10-16T13:06:34Z
department:
- _id: '34'
- _id: '819'
doi: 10.1177/2056305120939264
intvolume: ' 6'
issue: '3'
language:
- iso: eng
page: '2056305120939264'
publication: Social Media + Society
status: public
title: 'Demystifying Social Bots: On the Intelligence of Automated Social Media Actors'
type: journal_article
user_id: '15504'
volume: 6
year: '2020'
...
---
_id: '46332'
abstract:
- lang: eng
text: Multimodality is one of the biggest difficulties for optimization as local
optima are often preventing algorithms from making progress. This does not only
challenge local strategies that can get stuck. It also hinders meta-heuristics
like evolutionary algorithms in convergence to the global optimum. In this paper
we present a new concept of gradient descent, which is able to escape local traps.
It relies on multiobjectivization of the original problem and applies the recently
proposed and here slightly modified multi-objective local search mechanism MOGSA.
We use a sophisticated visualization technique for multi-objective problems to
prove the working principle of our idea. As such, this work highlights the transfer
of new insights from the multi-objective to the single-objective domain and provides
first visual evidence that multiobjectivization can link single-objective local
optima in multimodal landscapes.
author:
- first_name: Vera
full_name: Steinhoff, Vera
last_name: Steinhoff
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Pelin
full_name: Aspar, Pelin
last_name: Aspar
- 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: 'Steinhoff V, Kerschke P, Aspar P, Trautmann H, Grimme C. Multiobjectivization
of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient
Descent. In: Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI). ; 2020:2445–2452. doi:10.1109/SSCI47803.2020.9308259'
apa: 'Steinhoff, V., Kerschke, P., Aspar, P., Trautmann, H., & Grimme, C. (2020).
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From
Multi-Objective Gradient Descent. Proceedings of the IEEE Symposium Series
on Computational Intelligence (SSCI), 2445–2452. https://doi.org/10.1109/SSCI47803.2020.9308259'
bibtex: '@inproceedings{Steinhoff_Kerschke_Aspar_Trautmann_Grimme_2020, place={Canberra,
Australia}, title={Multiobjectivization of Local Search: Single-Objective Optimization
Benefits From Multi-Objective Gradient Descent}, DOI={10.1109/SSCI47803.2020.9308259},
booktitle={Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI)}, author={Steinhoff, Vera and Kerschke, Pascal and Aspar, Pelin and Trautmann,
Heike and Grimme, Christian}, year={2020}, pages={2445–2452} }'
chicago: 'Steinhoff, Vera, Pascal Kerschke, Pelin Aspar, Heike Trautmann, and Christian
Grimme. “Multiobjectivization of Local Search: Single-Objective Optimization Benefits
From Multi-Objective Gradient Descent.” In Proceedings of the IEEE Symposium
Series on Computational Intelligence (SSCI), 2445–2452. Canberra, Australia,
2020. https://doi.org/10.1109/SSCI47803.2020.9308259.'
ieee: 'V. Steinhoff, P. Kerschke, P. Aspar, H. Trautmann, and C. Grimme, “Multiobjectivization
of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient
Descent,” in Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI), 2020, pp. 2445–2452, doi: 10.1109/SSCI47803.2020.9308259.'
mla: 'Steinhoff, Vera, et al. “Multiobjectivization of Local Search: Single-Objective
Optimization Benefits From Multi-Objective Gradient Descent.” Proceedings of
the IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp.
2445–2452, doi:10.1109/SSCI47803.2020.9308259.'
short: 'V. Steinhoff, P. Kerschke, P. Aspar, H. Trautmann, C. Grimme, in: Proceedings
of the IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia,
2020, pp. 2445–2452.'
date_created: 2023-08-04T07:40:33Z
date_updated: 2023-10-16T13:05:49Z
department:
- _id: '34'
- _id: '819'
doi: 10.1109/SSCI47803.2020.9308259
language:
- iso: eng
page: 2445–2452
place: Canberra, Australia
publication: Proceedings of the IEEE Symposium Series on Computational Intelligence
(SSCI)
status: public
title: 'Multiobjectivization of Local Search: Single-Objective Optimization Benefits
From Multi-Objective Gradient Descent'
type: conference
user_id: '15504'
year: '2020'
...
---
_id: '48301'
author:
- first_name: Max
full_name: Glockner, Max
last_name: Glockner
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
- first_name: Iryna
full_name: Gurevych, Iryna
last_name: Gurevych
citation:
ama: 'Glockner M, Habernal I, Gurevych I. Why do you think that? Exploring Faithful
Sentence-Level Rationales Without Supervision. In: Findings of the Association
for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics;
2020. doi:10.18653/v1/2020.findings-emnlp.97'
apa: 'Glockner, M., Habernal, I., & Gurevych, I. (2020). Why do you think that?
Exploring Faithful Sentence-Level Rationales Without Supervision. Findings
of the Association for Computational Linguistics: EMNLP 2020. https://doi.org/10.18653/v1/2020.findings-emnlp.97'
bibtex: '@inproceedings{Glockner_Habernal_Gurevych_2020, title={Why do you think
that? Exploring Faithful Sentence-Level Rationales Without Supervision}, DOI={10.18653/v1/2020.findings-emnlp.97},
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2020},
publisher={Association for Computational Linguistics}, author={Glockner, Max and
Habernal, Ivan and Gurevych, Iryna}, year={2020} }'
chicago: 'Glockner, Max, Ivan Habernal, and Iryna Gurevych. “Why Do You Think That?
Exploring Faithful Sentence-Level Rationales Without Supervision.” In Findings
of the Association for Computational Linguistics: EMNLP 2020. Association
for Computational Linguistics, 2020. https://doi.org/10.18653/v1/2020.findings-emnlp.97.'
ieee: 'M. Glockner, I. Habernal, and I. Gurevych, “Why do you think that? Exploring
Faithful Sentence-Level Rationales Without Supervision,” 2020, doi: 10.18653/v1/2020.findings-emnlp.97.'
mla: 'Glockner, Max, et al. “Why Do You Think That? Exploring Faithful Sentence-Level
Rationales Without Supervision.” Findings of the Association for Computational
Linguistics: EMNLP 2020, Association for Computational Linguistics, 2020,
doi:10.18653/v1/2020.findings-emnlp.97.'
short: 'M. Glockner, I. Habernal, I. Gurevych, in: Findings of the Association for
Computational Linguistics: EMNLP 2020, Association for Computational Linguistics,
2020.'
date_created: 2023-10-19T08:29:15Z
date_updated: 2023-10-19T12:10:18Z
department:
- _id: '34'
- _id: '820'
doi: 10.18653/v1/2020.findings-emnlp.97
language:
- iso: eng
publication: 'Findings of the Association for Computational Linguistics: EMNLP 2020'
publication_status: published
publisher: Association for Computational Linguistics
status: public
title: Why do you think that? Exploring Faithful Sentence-Level Rationales Without
Supervision
type: conference
user_id: '15504'
year: '2020'
...