When proxy-driven learning is no better than random: The consequences of representational incompleteness
Machine learning is widely used for personalisation, that is, to tune systems with the aim of adapting their behaviour to the responses of humans. This tuning relies on quantified features that capture the human actions, and also on objective functions—that is, proxies – that are intended to represe...
| المؤلفون الرئيسيون: | , , |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Public Library of Science (PLoS)
2022-01-01
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| سلاسل: | PLoS ONE |
| الوصول للمادة أونلاين: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9278777/?tool=EBI |