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Philipp Schmidt
Philipp Schmidt
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Title
Cited by
Cited by
Year
Automating large-scale data quality verification
S Schelter, D Lange, P Schmidt, M Celikel, F Biessmann, A Grafberger
Proceedings of the VLDB Endowment 11 (12), 1781-1794, 2018
2262018
Transparency and trust in artificial intelligence systems
P Schmidt, F Biessmann, T Teubner
Journal of Decision Systems 29 (4), 260-278, 2020
2062020
Quantifying interpretability and trust in machine learning systems
P Schmidt, F Biessmann
arXiv preprint arXiv:1901.08558, 2019
1252019
DataWig: Missing value imputation for tables
F Biessmann, T Rukat, P Schmidt, P Naidu, S Schelter, A Taptunov, ...
Journal of Machine Learning Research 20 (175), 1-6, 2019
1092019
" Deep" Learning for Missing Value Imputationin Tables with Non-numerical Data
F Biessmann, D Salinas, S Schelter, P Schmidt, D Lange
Proceedings of the 27th ACM international conference on information and …, 2018
872018
Calibrating human-ai collaboration: Impact of risk, ambiguity and transparency on algorithmic bias
P Schmidt, F Biessmann
Machine Learning and Knowledge Extraction: 4th IFIP TC 5, TC 12, WG 8.4, WG …, 2020
312020
Automated data validation in machine learning systems
F Biessmann, J Golebiowski, T Rukat, D Lange, P Schmidt
262021
Unit testing data with deequ
S Schelter, F Biessmann, D Lange, T Rukat, P Schmidt, S Seufert, ...
Proceedings of the 2019 International Conference on Management of Data, 1993 …, 2019
202019
Deequ-data quality validation for machine learning pipelines
S Schelter, P Schmidt, T Rukat, M Kiessling, A Taptunov, F Biessmann, ...
202018
Differential data quality verification on partitioned data
S Schelter, S Grafberger, P Schmidt, T Rukat, M Kiessling, A Taptunov, ...
2019 IEEE 35th International Conference on Data Engineering (ICDE), 1940-1945, 2019
192019
Transparency
P Schmidt
The Sage Encyclopedia of Surveillance, Security and Privacy. Los Angeles: Sage, 2018
162018
Quantifying Interpretability and Trust in Machine Learning Systems.(2019)
P Schmidt, F Biessmann
Citado na, 57, 1901
91901
Quantifying interpretability and trust in machine learning systems. arXiv 2019
P Schmidt, F Biessmann
arXiv preprint arXiv:1901.08558, 0
6
More than words: Towards better quality interpretations of text classifiers
MB Zafar, P Schmidt, M Donini, C Archambeau, F Biessmann, SR Das, ...
arXiv preprint arXiv:2112.12444, 2021
52021
Learning action embeddings for off-policy evaluation
M Cief, J Golebiowski, P Schmidt, Z Abedjan, A Bekasov
European Conference on Information Retrieval, 108-122, 2024
22024
Variational boosted soft trees
T Cinquin, T Rukat, P Schmidt, M Wistuba, A Bekasov
International Conference on Artificial Intelligence and Statistics, 5787-5801, 2023
12023
More Than Words: Towards Better Quality Interpretations of Text Classifiers
M Bilal Zafar, P Schmidt, M Donini, C Archambeau, F Biessmann, ...
arXiv e-prints, arXiv: 2112.12444, 2021
2021
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Articles 1–17