Estimating individual treatment effect: generalization bounds and algorithms

No abstract is available for this paper.

• Publication year

  2016

• Venue

  International Conference on Machine Learning

• Publication date

  2016-06-13

• Fields of study

  Mathematics, Computer Science, Economics

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Supplemental Materials for : Estimating individual treatment effect : generalization bounds and algorithms

  2017cited by this paper
• Preconditioning of Optimal Transport

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• Learning Representations for Counterfactual Inference

  2016influential reference
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