Thesis - Enhancing Machine Learning Transparency through Data Attribution
at Produktionstechnik und Automatisierung
70569 Stuttgart, Baden-Württemberg, Germany -
| Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
|---|---|---|---|---|---|---|---|
| Immediate | 18 Jul, 2024 | Not Specified | 18 Apr, 2024 | N/A | Good communication skills | No | No |
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| Full Time | Part Time |
| Permanent | Independent - 1099 |
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Description:
Die Fraunhofer-Gesellschaft betreibt in Deutschland derzeit 76 Institute und Forschungseinrichtungen und ist die weltweit führende Organisation für anwendungsorientierte Forschung. Rund 30 800 Mitarbeitende erarbeiten das jährliche Forschungsvolumen von 3,0 Milliarden Euro.
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Explaining the predictions of ML models remains an important yet challenging task for the successful application of ML-based solutions, especially in safety-critical domains. A rather novel method is data attribution, where specific test predictions are attributed to the training data. We are interested in practical applications of these methods to ensure the safety and reliability of ML in real-world scenarios.
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REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
70569 Stuttgart, Germany
