7.4k citations · 22.9k across the 86 of their papers we have counts for
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stat.ML2017★ 56 cited
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer
David Madras, Toniann Pitassi, Richard Zemel
In many machine learning applications, there are multiple decision-makers involved, both automated and human. The interaction between these agents often goes unaddressed in algorit…
stat.ML2017★ 281 cited
Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos, Uri Shalit, Joris Mooij +3
Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for pol…