论文标题
在中间响应下进行分布概括的不变匹配属性
An Invariant Matching Property for Distribution Generalization under Intervened Response
论文作者
论文摘要
分配概括的任务涉及在看不见的环境中对响应的可靠预测。结构性因果模型被证明可用于通过干预模型变化。受基本不变性原则的启发，通常假定响应的条件分布在整个环境之间保持不变。但是，当响应干预时，在实际情况下可能会违反此假设。在这项工作中，我们研究了一类具有中间响应的模型。我们通过将某些特征的估计值合并为其他预测因素来确定一种新型的不变性形式。有效地，我们表明这种不变性等同于具有使概括成为可能的确定性线性匹配。我们提供了线性匹配的明确表征，并在各种干预设置下介绍了我们的仿真结果。
The task of distribution generalization concerns making reliable prediction of a response in unseen environments. The structural causal models are shown to be useful to model distribution changes through intervention. Motivated by the fundamental invariance principle, it is often assumed that the conditional distribution of the response given its predictors remains the same across environments. However, this assumption might be violated in practical settings when the response is intervened. In this work, we investigate a class of model with an intervened response. We identify a novel form of invariance by incorporating the estimates of certain features as additional predictors. Effectively, we show this invariance is equivalent to having a deterministic linear matching that makes the generalization possible. We provide an explicit characterization of the linear matching and present our simulation results under various intervention settings.
