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cs.LG2024
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance
Thomas Decker, Alexander Koebler, Michael Lebacher +3
Monitoring and maintaining machine learning models are among the most critical challenges in translating recent advances in the field into real-world applications. However, current…
cs.LG2024
Provably Better Explanations with Optimized Aggregation of Feature Attributions
Thomas Decker, Ananta R. Bhattarai, Jindong Gu +2
Using feature attributions for post-hoc explanations is a common practice to understand and verify the predictions of opaque machine learning models. Despite the numerous technique…