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 23:53, 18 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].