Learning Through the Lens of Robustness
Despite their impressive performance on large-scale benchmarks, machine learning sys- tems turn out to be quite brittle outside of the exact setting in which they were developed. How can we build ML models that are robust and reliable enough for real-world deployment? To answer this question,...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/140148 |
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