20 citations · 58 across the 10 of their papers we have counts for
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cs.LG2019
Feature Noise Induces Loss Discrepancy Across Groups
Fereshte Khani, Percy Liang
The performance of standard learning procedures has been observed to differ widely across groups. Recent studies usually attribute this loss discrepancy to an information deficienc…
cs.LG2019★ 5 cited
Maximum Weighted Loss Discrepancy
Fereshte Khani, Aditi Raghunathan, Percy Liang
Though machine learning algorithms excel at minimizing the average loss over a population, this might lead to large discrepancies between the losses across groups within the popula…