• Corpus ID: 246680177

Generative multitask learning mitigates target-causing confounding

  title={Generative multitask learning mitigates target-causing confounding},
  author={Taro Makino and Krzysztof J Geras and Kyunghyun Cho},
We propose a simple and scalable approach to causal representation learning for multitask learning. Our approach requires minimal modification to existing ML systems, and improves robustness to target shift. The improvement comes from mitigating unobserved confounders that cause the targets, but not the input. We refer to them as target-causing confounders. These confounders induce spurious dependencies between the input and targets. This poses a problem for the conventional approach to… 
1 Citations

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