Learning to Personalize from Observational Data

By Nathan Kallus. 2016

9 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Susan Athey
2. Stefan Wager
3. Julie Tibshirani
4. Xinkun Nie
5. Ahmed M. Alaa
6. Guido W. Imbens
7. Nathan Kallus
8. Victor Chernozhukov

Citations in the corpus

• Generalized random forests (2016, background): “…for other problems, including Athey and Imbens (2016) and Su et al. (2009) for treatment effect estimation, Beygelzimer and Langford (2009) and Kallus (2016) for personalized policy allocation, and Gordon and Olshen (1985), LeBlanc and Crowley (1992), Molinaro, Dudoit and Van der Laan (2004)…”
• Efficient Policy Learning (2017, methodology): “…learning using a single “batch” dataset collected before running any analysis (Beygelzimer and Langford, 2009; Chen et al., 2016; Bottou et al., 2013; Kallus, 2016; Kitagawa and Tetenov, 2015; Dud́ık et al., 2011; Swaminathan and Joachims, 2015; Qian and Murphy, 2011; Zhang et al., 2012; Zhao et…”