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ORCIDChristoph Kern 0001
Person information
- affiliation: Ludwig Maximilian University of Munich, Germany
Other persons with the same name
- Christoph Kern — disambiguation page
- Christoph Kern 0002 — TU Wien, Vienna, Austria
- Christoph Kern 0003 — Google's Security Foundations organization, Seattle, WA, USA
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Journal Articles
- 2024
[j5]Patrick Oliver Schenk, Christoph Kern:
Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production. AStA Wirtschafts und Sozialstatistisches Arch. 18(2): 131-184 (2024)- [j4]Unai Fischer Abaigar, Christoph Kern, Noam Barda, Frauke Kreuter:
Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector. Gov. Inf. Q. 41(4): 101976 (2024) - 2022
- [j3]Frederic Gerdon
, Ruben L. Bach, Christoph Kern, Frauke Kreuter:
Social impacts of algorithmic decision-making: A research agenda for the social sciences. Big Data Soc. 9(1): 205395172210893 (2022) - [j2]Christoph Kern, Frederic Gerdon, Ruben L. Bach, Florian Keusch, Frauke Kreuter:
Humans versus machines: Who is perceived to decide fairer? Experimental evidence on attitudes toward automated decision-making. Patterns 3(10): 100591 (2022) - 2021
- [j1]Florian Pfisterer, Christoph Kern, Susanne Dandl, Matthew Sun, Michael Kim, Bernd Bischl:
mcboost: Multi-Calibration Boosting for R. J. Open Source Softw. 6(64): 3453 (2021)
Conference and Workshop Papers
- 2024
- [c8]Sofia Jaime, Christoph Kern:
Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice. FAccT 2024: 237-253 - [c7]Jan Simson, Alessandro Fabris, Christoph Kern:
Lazy Data Practices Harm Fairness Research. FAccT 2024: 642-659 - [c6]Jan Simson, Florian Pfisterer, Christoph Kern:
One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions. FAccT 2024: 1305-1320 - 2023
- [c5]Christoph Kern, Stephanie Eckman, Jacob Beck, Rob Chew, Bolei Ma, Frauke Kreuter:
Annotation Sensitivity: Training Data Collection Methods Affect Model Performance. EMNLP (Findings) 2023: 14874-14886 - [c4]Sofia Jaime, Christoph Kern:
Ethnic Classifications in Algorithmic Decision-Making Processes. EWAF 2023 - [c3]Christoph Kern, Ruben L. Bach, Hannah Mautner, Frauke Kreuter:
When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes. EWAF 2023 - [c2]Jan Simson, Florian Pfisterer, Christoph Kern:
What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. EWAF 2023 - [c1]Jan Simson, Florian Pfisterer, Christoph Kern:
Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. HHAI 2023: 382-384
Data and Artifacts
- 2021
- [d1]Florian Pfisterer, Christoph Kern, Susanne Dandl, Mathew Sun, Michael P. Kim, Bernd Bischl:
mcboost: Multi-Calibration Boosting for R. Zenodo, 2021
Informal and Other Publications
- 2024
- [i10]Patrick Oliver Schenk, Christoph Kern:
Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production. CoRR abs/2402.09328 (2024) - [i9]Jan Simson, Alessandro Fabris, Christoph Kern:
Lazy Data Practices Harm Fairness Research. CoRR abs/2404.17293 (2024) - [i8]Christoph Kern, Michael Kim, Angela Zhou:
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts. CoRR abs/2405.18206 (2024) - [i7]Unai Fischer Abaigar, Christoph Kern, Frauke Kreuter:
The Missing Link: Allocation Performance in Causal Machine Learning. CoRR abs/2407.10779 (2024) - 2023
- [i6]Jan Simson, Florian Pfisterer, Christoph Kern:
Everything, Everywhere All in One Evaluation: Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. CoRR abs/2308.16681 (2023) - [i5]Unai Fischer Abaigar, Christoph Kern, Noam Barda, Frauke Kreuter:
Bridging the Gap: Towards an Expanded Toolkit for ML-Supported Decision-Making in the Public Sector. CoRR abs/2310.19091 (2023) - [i4]Christoph Kern, Stephanie Eckman, Jacob Beck, Rob Chew, Bolei Ma, Frauke Kreuter:
Annotation Sensitivity: Training Data Collection Methods Affect Model Performance. CoRR abs/2311.14212 (2023) - 2022
- [i3]Patrick Kaiser, Christoph Kern, David Rügamer:
Uncertainty-aware predictive modeling for fair data-driven decisions. CoRR abs/2211.02730 (2022) - 2021
- [i2]Matthias Kuppler, Christoph Kern, Ruben L. Bach, Frauke Kreuter:
Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There? CoRR abs/2105.01441 (2021) - [i1]Christoph Kern, Ruben L. Bach, Hannah Mautner, Frauke Kreuter:
Fairness in Algorithmic Profiling: A German Case Study. CoRR abs/2108.04134 (2021)
Coauthor Index
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