Interpretability for Deep Learning Text Classifiers
The ubiquitous presence of automated decision-making systems that have a performance comparable to humans brought attention towards the necessity of interpretability for the generated predictions. Whether the goal is predicting the system’s behavior when the input changes, building user trust, or...
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| Format: | Others |
| Language: | en |
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Université d'Ottawa / University of Ottawa
2020
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| Online Access: | http://hdl.handle.net/10393/41564 http://dx.doi.org/10.20381/ruor-25786 |