Techniques for Interpretability and Transparency of Black-Box Models
The last decade witnessed immense progress in machine learning, which has been deployed in many domains such as healthcare, finance and justice. However, recent advances are largely powered by deep neural networks, whose opacity hinders people's ability to inspect these models. Furthermore, leg...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/150171 |