Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Causal Relationships from Conditional Moment Conditions by
  Importance Weighting   We consider learning causal relationships under conditional moment
conditions. Unlike causal inference under unconditional moment conditions,
conditional moment conditions pose serious challenges for causal inference,
especially in complex, high-dimensional settings. To address this issue, we
propose a method that transforms conditional moment conditions to unconditional
moment conditions through importance weighting using the conditional density
ratio. Then, using this transformation, we propose a method that successfully
approximates conditional moment conditions. Our proposed approach allows us to
employ methods for estimating causal parameters from unconditional moment
conditions, such as generalized method of moments, adequately in a
straightforward manner. In experiments, we confirm that our proposed method
performs well compared to existing methods.

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The categories of this paper are: cond-mat
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The categories of this paper are: eess
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th