1 citations · 1 across the 7 of their papers we have counts for
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Treatment Effect Modification by Latent Classes
Hui Lan, Nathan Kallus, Winston Chou
Many treatments have effects that plausibly vary by latent classes. For example, the effect of personalized video recommendations may be stronger for users who seek a new discovery…
Policy Learning with Weak Signals
Benedikt Koch, Winston Chou, Aurélien Bibaut +1
Policy learning in digital experimentation faces three challenges: weak signal-to-noise ratios, rich covariate spaces, and massive data volumes. We formalize this regime by modelin…
Blending Proxy Metrics with a North Star
Winston Chou
Proxy metrics are widely used to improve the precision and velocity of online experimentation (aka A/B testing). Although proxies are often motivated by long-term outcomes that the…
Evaluating Decision Rules Across Many Weak Experiments
Winston Chou, Colin Gray, Nathan Kallus +2
Technology firms conduct randomized controlled experiments ("A/B tests") to learn which actions to take to improve business outcomes. In firms with mature experimentation platforms…
Learning the Covariance of Treatment Effects Across Many Weak Experiments
Aurélien Bibaut, Winston Chou, Simon Ejdemyr +1
When primary objectives are insensitive or delayed, experimenters may instead focus on proxy metrics derived from secondary outcomes. For example, technology companies often infer…