HyDRA: hypergradient data relevance analysis for interpreting deep neural networks.
The behaviors of deep neural networks (DNNs) are notoriously resistant to human interpretations. In this paper, we propose Hypergradient Data Relevance Analysis, or HYDRA, which interprets the predictions made by DNNs as effects of their training data. Existing approaches generally estimate data con...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://aaai.org/Conferences/AAAI-21/ https://hdl.handle.net/10356/147652 |