Heterogeneous Risk Minimization
Jiashuo Liu 1 Zheyuan Hu 1 Peng Cui 1 Bo Li 2 Zheyan Shen 1
Abstract with ERM usually suffer from poor generalization perfor-
mance due to the greedy exploitation of correlations among
Machine learning algorithms with empirical risk
the training data, which are not stable under distributional
minimization usually suffer from poor generaliza-
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