---
_id: '25209'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Diego
  full_name: Moussallem, Diego
  last_name: Moussallem
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Moussallem D, Ngonga Ngomo A-C. A shallow neural model for relation
    prediction. <i>CoRR</i>. 2021;abs/2101.09090.
  apa: Demir, C., Moussallem, D., &#38; Ngonga Ngomo, A.-C. (2021). A shallow neural
    model for relation prediction. <i>CoRR</i>, <i>abs/2101.09090</i>.
  bibtex: '@article{Demir_Moussallem_Ngonga Ngomo_2021, title={A shallow neural model
    for relation prediction}, volume={abs/2101.09090}, journal={CoRR}, author={Demir,
    Caglar and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2021} }'
  chicago: Demir, Caglar, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “A Shallow
    Neural Model for Relation Prediction.” <i>CoRR</i> abs/2101.09090 (2021).
  ieee: C. Demir, D. Moussallem, and A.-C. Ngonga Ngomo, “A shallow neural model for
    relation prediction,” <i>CoRR</i>, vol. abs/2101.09090, 2021.
  mla: Demir, Caglar, et al. “A Shallow Neural Model for Relation Prediction.” <i>CoRR</i>,
    vol. abs/2101.09090, 2021.
  short: C. Demir, D. Moussallem, A.-C. Ngonga Ngomo, CoRR abs/2101.09090 (2021).
date_created: 2021-10-01T06:50:02Z
date_updated: 2022-01-06T06:56:55Z
department:
- _id: '574'
language:
- iso: eng
publication: CoRR
status: public
title: A shallow neural model for relation prediction
type: journal_article
user_id: '65716'
volume: abs/2101.09090
year: '2021'
...
---
_id: '25213'
author:
- first_name: Arnab
  full_name: Sharma, Arnab
  id: '67200'
  last_name: Sharma
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
- first_name: Heike
  full_name: Wehrheim, Heike
  id: '573'
  last_name: Wehrheim
citation:
  ama: Sharma A, Demir C, Ngonga Ngomo A-C, Wehrheim H. MLCheck- Property-Driven Testing
    of Machine Learning Models. <i>CoRR</i>. 2021;abs/2105.00741.
  apa: Sharma, A., Demir, C., Ngonga Ngomo, A.-C., &#38; Wehrheim, H. (2021). MLCheck-
    Property-Driven Testing of Machine Learning Models. <i>CoRR</i>, <i>abs/2105.00741</i>.
  bibtex: '@article{Sharma_Demir_Ngonga Ngomo_Wehrheim_2021, title={MLCheck- Property-Driven
    Testing of Machine Learning Models}, volume={abs/2105.00741}, journal={CoRR},
    author={Sharma, Arnab and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille and Wehrheim,
    Heike}, year={2021} }'
  chicago: Sharma, Arnab, Caglar Demir, Axel-Cyrille Ngonga Ngomo, and Heike Wehrheim.
    “MLCheck- Property-Driven Testing of Machine Learning Models.” <i>CoRR</i> abs/2105.00741
    (2021).
  ieee: A. Sharma, C. Demir, A.-C. Ngonga Ngomo, and H. Wehrheim, “MLCheck- Property-Driven
    Testing of Machine Learning Models,” <i>CoRR</i>, vol. abs/2105.00741, 2021.
  mla: Sharma, Arnab, et al. “MLCheck- Property-Driven Testing of Machine Learning
    Models.” <i>CoRR</i>, vol. abs/2105.00741, 2021.
  short: A. Sharma, C. Demir, A.-C. Ngonga Ngomo, H. Wehrheim, CoRR abs/2105.00741
    (2021).
date_created: 2021-10-01T06:54:10Z
date_updated: 2022-01-06T06:56:55Z
department:
- _id: '574'
language:
- iso: eng
publication: CoRR
status: public
title: MLCheck- Property-Driven Testing of Machine Learning Models
type: journal_article
user_id: '65716'
volume: abs/2105.00741
year: '2021'
...
---
_id: '25215'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Ngonga Ngomo A-C. Out-of-Vocabulary Entities in Link Prediction. <i>CoRR</i>.
    2021;abs/2105.12524.
  apa: Demir, C., &#38; Ngonga Ngomo, A.-C. (2021). Out-of-Vocabulary Entities in
    Link Prediction. <i>CoRR</i>, <i>abs/2105.12524</i>.
  bibtex: '@article{Demir_Ngonga Ngomo_2021, title={Out-of-Vocabulary Entities in
    Link Prediction}, volume={abs/2105.12524}, journal={CoRR}, author={Demir, Caglar
    and Ngonga Ngomo, Axel-Cyrille}, year={2021} }'
  chicago: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Out-of-Vocabulary Entities
    in Link Prediction.” <i>CoRR</i> abs/2105.12524 (2021).
  ieee: C. Demir and A.-C. Ngonga Ngomo, “Out-of-Vocabulary Entities in Link Prediction,”
    <i>CoRR</i>, vol. abs/2105.12524, 2021.
  mla: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Out-of-Vocabulary Entities in
    Link Prediction.” <i>CoRR</i>, vol. abs/2105.12524, 2021.
  short: C. Demir, A.-C. Ngonga Ngomo, CoRR abs/2105.12524 (2021).
date_created: 2021-10-01T06:55:36Z
date_updated: 2022-01-06T06:56:55Z
department:
- _id: '574'
language:
- iso: eng
publication: CoRR
status: public
title: Out-of-Vocabulary Entities in Link Prediction
type: journal_article
user_id: '65716'
volume: abs/2105.12524
year: '2021'
...
---
_id: '25217'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Ngonga Ngomo A-C. DRILL- Deep Reinforcement Learning for Refinement
    Operators in ALC. <i>CoRR</i>. 2021;abs/2106.15373.
  apa: Demir, C., &#38; Ngonga Ngomo, A.-C. (2021). DRILL- Deep Reinforcement Learning
    for Refinement Operators in ALC. <i>CoRR</i>, <i>abs/2106.15373</i>.
  bibtex: '@article{Demir_Ngonga Ngomo_2021, title={DRILL- Deep Reinforcement Learning
    for Refinement Operators in ALC}, volume={abs/2106.15373}, journal={CoRR}, author={Demir,
    Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2021} }'
  chicago: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “DRILL- Deep Reinforcement
    Learning for Refinement Operators in ALC.” <i>CoRR</i> abs/2106.15373 (2021).
  ieee: C. Demir and A.-C. Ngonga Ngomo, “DRILL- Deep Reinforcement Learning for Refinement
    Operators in ALC,” <i>CoRR</i>, vol. abs/2106.15373, 2021.
  mla: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “DRILL- Deep Reinforcement Learning
    for Refinement Operators in ALC.” <i>CoRR</i>, vol. abs/2106.15373, 2021.
  short: C. Demir, A.-C. Ngonga Ngomo, CoRR abs/2106.15373 (2021).
date_created: 2021-10-01T06:56:48Z
date_updated: 2022-01-06T06:56:55Z
department:
- _id: '574'
language:
- iso: eng
publication: CoRR
status: public
title: DRILL- Deep Reinforcement Learning for Refinement Operators in ALC
type: journal_article
user_id: '65716'
volume: abs/2106.15373
year: '2021'
...
---
_id: '28350'
abstract:
- lang: eng
  text: "In recent years, we observe an increasing amount of software with machine
    learning components being deployed. This poses the question of quality assurance
    for such components: how can we validate whether specified requirements are fulfilled
    by a machine learned software? Current testing and verification approaches either
    focus on a single requirement (e.g., fairness) or specialize on a single type
    of machine learning model (e.g., neural networks).\r\nIn this paper, we propose
    property-driven testing of machine learning models. Our approach MLCheck encompasses
    (1) a language for property specification, and (2) a technique for systematic
    test case generation. The specification language is comparable to property-based
    testing languages. Test case generation employs advanced verification technology
    for a systematic, property dependent construction of test suites, without additional
    user supplied generator functions. We evaluate MLCheck using requirements and
    data sets from three different application areas (software\r\ndiscrimination,
    learning on knowledge graphs and security). Our evaluation shows that despite
    its generality MLCheck can even outperform specialised testing approaches while
    having a comparable runtime"
author:
- first_name: Arnab
  full_name: Sharma, Arnab
  id: '67200'
  last_name: Sharma
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
- first_name: Heike
  full_name: Wehrheim, Heike
  id: '573'
  last_name: Wehrheim
citation:
  ama: 'Sharma A, Demir C, Ngonga Ngomo A-C, Wehrheim H. MLCHECK–Property-Driven Testing
    of Machine Learning Classifiers. In: <i>Proceedings of the 20th IEEE International
    Conference on Machine Learning and Applications (ICMLA)</i>. IEEE.'
  apa: Sharma, A., Demir, C., Ngonga Ngomo, A.-C., &#38; Wehrheim, H. (n.d.). MLCHECK–Property-Driven
    Testing of Machine Learning Classifiers. <i>Proceedings of the 20th IEEE International
    Conference on Machine Learning and Applications (ICMLA)</i>.
  bibtex: '@inproceedings{Sharma_Demir_Ngonga Ngomo_Wehrheim, title={MLCHECK–Property-Driven
    Testing of Machine Learning Classifiers}, booktitle={Proceedings of the 20th IEEE
    International Conference on Machine Learning and Applications (ICMLA)}, publisher={IEEE},
    author={Sharma, Arnab and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille and Wehrheim,
    Heike} }'
  chicago: Sharma, Arnab, Caglar Demir, Axel-Cyrille Ngonga Ngomo, and Heike Wehrheim.
    “MLCHECK–Property-Driven Testing of Machine Learning Classifiers.” In <i>Proceedings
    of the 20th IEEE International Conference on Machine Learning and Applications
    (ICMLA)</i>. IEEE, n.d.
  ieee: A. Sharma, C. Demir, A.-C. Ngonga Ngomo, and H. Wehrheim, “MLCHECK–Property-Driven
    Testing of Machine Learning Classifiers.”
  mla: Sharma, Arnab, et al. “MLCHECK–Property-Driven Testing of Machine Learning
    Classifiers.” <i>Proceedings of the 20th IEEE International Conference on Machine
    Learning and Applications (ICMLA)</i>, IEEE.
  short: 'A. Sharma, C. Demir, A.-C. Ngonga Ngomo, H. Wehrheim, in: Proceedings of
    the 20th IEEE International Conference on Machine Learning and Applications (ICMLA),
    IEEE, n.d.'
date_created: 2021-12-07T11:11:36Z
date_updated: 2022-01-06T06:58:02Z
department:
- _id: '7'
- _id: '77'
- _id: '574'
language:
- iso: eng
project:
- _id: '1'
  name: SFB 901
- _id: '3'
  name: SFB 901 - Project Area B
- _id: '11'
  name: SFB 901 - Subproject B3
- _id: '10'
  name: SFB 901 - Subproject B2
publication: Proceedings of the 20th IEEE International Conference on Machine Learning
  and Applications (ICMLA)
publication_status: accepted
publisher: IEEE
status: public
title: MLCHECK–Property-Driven Testing of Machine Learning Classifiers
type: conference
user_id: '477'
year: '2021'
...
---
_id: '29287'
abstract:
- lang: eng
  text: "Knowledge graph embedding research has mainly focused on the two smallest\r\nnormed
    division algebras, $\\mathbb{R}$ and $\\mathbb{C}$. Recent results suggest\r\nthat
    trilinear products of quaternion-valued embeddings can be a more effective\r\nmeans
    to tackle link prediction. In addition, models based on convolutions on\r\nreal-valued
    embeddings often yield state-of-the-art results for link\r\nprediction. In this
    paper, we investigate a composition of convolution\r\noperations with hypercomplex
    multiplications. We propose the four approaches\r\nQMult, OMult, ConvQ and ConvO
    to tackle the link prediction problem. QMult and\r\nOMult can be considered as
    quaternion and octonion extensions of previous\r\nstate-of-the-art approaches,
    including DistMult and ComplEx. ConvQ and ConvO\r\nbuild upon QMult and OMult
    by including convolution operations in a way\r\ninspired by the residual learning
    framework. We evaluated our approaches on\r\nseven link prediction datasets including
    WN18RR, FB15K-237 and YAGO3-10.\r\nExperimental results suggest that the benefits
    of learning hypercomplex-valued\r\nvector representations become more apparent
    as the size and complexity of the\r\nknowledge graph grows. ConvO outperforms
    state-of-the-art approaches on\r\nFB15K-237 in MRR, Hit@1 and Hit@3, while QMult,
    OMult, ConvQ and ConvO\r\noutperform state-of-the-approaches on YAGO3-10 in all
    metrics. Results also\r\nsuggest that link prediction performances can be further
    improved via\r\nprediction averaging. To foster reproducible research, we provide
    an\r\nopen-source implementation of approaches, including training and evaluation\r\nscripts
    as well as pretrained models."
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Diego
  full_name: Moussallem, Diego
  id: '71635'
  last_name: Moussallem
- first_name: Stefan
  full_name: Heindorf, Stefan
  id: '11871'
  last_name: Heindorf
  orcid: 0000-0002-4525-6865
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: 'Demir C, Moussallem D, Heindorf S, Ngonga Ngomo A-C. Convolutional Hypercomplex
    Embeddings for Link Prediction. In: <i>The 13th Asian Conference on Machine Learning,
    ACML 2021</i>. ; 2021.'
  apa: Demir, C., Moussallem, D., Heindorf, S., &#38; Ngonga Ngomo, A.-C. (2021).
    Convolutional Hypercomplex Embeddings for Link Prediction. <i>The 13th Asian Conference
    on Machine Learning, ACML 2021</i>.
  bibtex: '@inproceedings{Demir_Moussallem_Heindorf_Ngonga Ngomo_2021, title={Convolutional
    Hypercomplex Embeddings for Link Prediction}, booktitle={The 13th Asian Conference
    on Machine Learning, ACML 2021}, author={Demir, Caglar and Moussallem, Diego and
    Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}, year={2021} }'
  chicago: Demir, Caglar, Diego Moussallem, Stefan Heindorf, and Axel-Cyrille Ngonga
    Ngomo. “Convolutional Hypercomplex Embeddings for Link Prediction.” In <i>The
    13th Asian Conference on Machine Learning, ACML 2021</i>, 2021.
  ieee: C. Demir, D. Moussallem, S. Heindorf, and A.-C. Ngonga Ngomo, “Convolutional
    Hypercomplex Embeddings for Link Prediction,” 2021.
  mla: Demir, Caglar, et al. “Convolutional Hypercomplex Embeddings for Link Prediction.”
    <i>The 13th Asian Conference on Machine Learning, ACML 2021</i>, 2021.
  short: 'C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian
    Conference on Machine Learning, ACML 2021, 2021.'
date_created: 2022-01-12T10:21:10Z
date_updated: 2022-10-17T15:06:40Z
department:
- _id: '574'
external_id:
  arxiv:
  - '2106.15230'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://papers.dice-research.org/2021/ACML2021_HyperConv/public.pdf
oa: '1'
publication: The 13th Asian Conference on Machine Learning, ACML 2021
status: public
title: Convolutional Hypercomplex Embeddings for Link Prediction
type: conference
user_id: '11871'
year: '2021'
...
---
_id: '25350'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Ngonga Ngomo A-C. A Physical Embedding Model for Knowledge Graphs.
    <i>CoRR</i>. 2020;abs/2001.07418.
  apa: Demir, C., &#38; Ngonga Ngomo, A.-C. (2020). A Physical Embedding Model for
    Knowledge Graphs. <i>CoRR</i>, <i>abs/2001.07418</i>.
  bibtex: '@article{Demir_Ngonga Ngomo_2020, title={A Physical Embedding Model for
    Knowledge Graphs}, volume={abs/2001.07418}, journal={CoRR}, author={Demir, Caglar
    and Ngonga Ngomo, Axel-Cyrille}, year={2020} }'
  chicago: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “A Physical Embedding Model
    for Knowledge Graphs.” <i>CoRR</i> abs/2001.07418 (2020).
  ieee: C. Demir and A.-C. Ngonga Ngomo, “A Physical Embedding Model for Knowledge
    Graphs,” <i>CoRR</i>, vol. abs/2001.07418, 2020.
  mla: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “A Physical Embedding Model for
    Knowledge Graphs.” <i>CoRR</i>, vol. abs/2001.07418, 2020.
  short: C. Demir, A.-C. Ngonga Ngomo, CoRR abs/2001.07418 (2020).
date_created: 2021-10-04T20:49:21Z
date_updated: 2022-01-06T06:57:01Z
language:
- iso: eng
publication: CoRR
status: public
title: A Physical Embedding Model for Knowledge Graphs
type: journal_article
user_id: '15526'
volume: abs/2001.07418
year: '2020'
...