Philipp Schmidt
Philipp Schmidt
Verified email at amazon.com
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
492018
Quantifying interpretability and trust in machine learning systems
P Schmidt, F Biessmann
arXiv preprint arXiv:1901.08558, 2019
182019
Deep Learning for Missing Value Imputation in 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
162018
" 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
132018
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
62019
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
42019
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
32019
Transparency and trust in artificial intelligence systems
P Schmidt, F Biessmann, T Teubner
Journal of Decision Systems, 1-19, 2020
12020
Deequ-Data Quality Validation for Machine Learning Pipelines
S Schelter, S Grafberger, P Schmidt, T Rukat, M Kiessling, A Taptunov, ...
12018
Calibrating Human-AI Collaboration: Impact of Risk, Ambiguity and Transparency on Algorithmic Bias
P Schmidt, F Biessmann
International Cross-Domain Conference for Machine Learning and Knowledge …, 2020
2020
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Articles 1–10