Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
In real-world machine learning applications, data subsets correspond to especially critical outcomes: vulnerable cyclist detections are safety-critical in an autonomous driving task, and "question" sentences might be important to a dialogue agent's language understanding for product purposes. While machine learning models can achieve high quality p...
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Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
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TN_cdi_proquest_journals_2291102229
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2291102229
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E-ISSN
2331-8422
