guide:B6a5cd7faf: Difference between revisions

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In this chapter, we have learned about the following topics:
<ul><li> Average treatment effect;
  </li>
<li> Regression for causal inference;
  </li>
<li> Randomized controlled trials;
  </li>
<li> Outcome maximization with a bandit algorithm;
  </li>
<li> A contextual bandit.
</li>
</ul>


==General references==
{{cite arXiv|last1=Cho|first1=Kyunghyun|year=2024|title=A Brief Introduction to  Causal Inference in Machine Learning|eprint=2405.08793|class=cs.LG}}

Latest revision as of 00:53, 19 May 2024

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In this chapter, we have learned about the following topics:

  • Average treatment effect;
  • Regression for causal inference;
  • Randomized controlled trials;
  • Outcome maximization with a bandit algorithm;
  • A contextual bandit.

General references

Cho, Kyunghyun (2024). "A Brief Introduction to Causal Inference in Machine Learning". arXiv:2405.08793 [cs.LG].