Ada – Advanced Algorithms for an Artificial Data Analyst
At a glance
- Project leader : Prof. Dr. Thilo Stadelmann
- Project team : Mohammadreza Amirian, Dr. Fernando Benites de Azevedo e Souza, Katharina Rombach, Lukas Tuggener
- Project budget : CHF 935'000
- Project status : completed
- Funding partner : CTI (KTI-Projekt / Projekt Nr. 25948.1 PFES-ES)
- Project partner : PricewaterhouseCoopers PwC AG (Zürich), Ecole polytechnique fédérale de Lausanne EPFL / Machine Learning and Optimization Laboratory
- Contact person : Thilo Stadelmann
Publications
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Amirian, Mohammadreza; Tuggener, Lukas; Chavarriaga, Ricardo; Satyawan, Yvan Putra; Schilling, Frank-Peter; Schwenker, Friedhelm; Stadelmann, Thilo,
2021.
Two to trust : AutoML for safe modelling and interpretable deep learning for robustness [paper].
In:
Postproceedings of the 1st TAILOR Workshop on Trustworthy AI at ECAI 2020.
1st TAILOR Workshop on Trustworthy AI at ECAI 2020, Santiago de Compostela, Spain, 29-30 August 2020.
Springer.
Available from: https://doi.org/10.21256/zhaw-22061
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Tuggener, Lukas; Amirian, Mohammadreza; Benites de Azevedo e Souza, Fernando; von Däniken, Pius; Gupta, Prakhar; Schilling, Frank-Peter; Stadelmann, Thilo,
2020.
Design patterns for resource-constrained automated deep-learning methods.
AI.
1(4), pp. 510-538.
Available from: https://doi.org/10.3390/ai1040031
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Tuggener, Lukas; Amirian, Mohammadreza; Rombach, Katharina; Lörwald, Stefan; Varlet, Anastasia; Westermann, Christian; Stadelmann, Thilo,
2019.
Automated machine learning in practice : state of the art and recent results [paper].
In:
2019 6th Swiss Conference on Data Science (SDS).
6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019.
IEEE.
pp. 31-36.
Available from: https://doi.org/10.1109/SDS.2019.00-11
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Amirian, Mohammadreza; Rombach, Katharina; Tuggener, Lukas; Schilling, Frank-Peter; Stadelmann, Thilo,
2019.
Efficient deep CNNs for cross-modal automated computer vision under time and space constraints [paper].
In:
ECML-PKDD 2019, Würzburg, Germany, 16-19 September 2019.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-18357