Causality-inspired comparative learning supervised model for domain generalization
Xiaosong Zhu,
Bin Yang,
Jingfeng Guo
et al.
Abstract:Machine learning is good at learning general knowledge and predictive knowledge from known and limited environments, and perform well in similar environments. However, their performance in unknown environments is not satisfactory. Machine learning focus on correlation learning, but correlation is not causality. The non-causal part of the correlation forms spurious correlation that affect the model's generalization ability. Therefore, it is necessary to examine machine learning from a causal perspective. By con… Show more
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