54 citations · 54 across the 1 of their papers we have counts for
3 papers
cs.LG2024
Class flipping for uplift modeling and Heterogeneous Treatment Effect estimation on imbalanced RCT data
Krzysztof Rudaś, Szymon Jaroszewicz
Uplift modeling and Heterogeneous Treatment Effect (HTE) estimation aim at predicting the causal effect of an action, such as a medical treatment or a marketing campaign on a speci…
cs.LG2019★ 54 cited
Response Transformation and Profit Decomposition for Revenue Uplift Modeling
Robin M. Gubela, Stefan Lessmann, Szymon Jaroszewicz
Uplift models support decision-making in marketing campaign planning. Estimating the causal effect of a marketing treatment, an uplift model facilitates targeting communication to…
cs.LG2018
Boosting algorithms for uplift modeling
Michał Sołtys, Szymon Jaroszewicz
Uplift modeling is an area of machine learning which aims at predicting the causal effect of some action on a given individual. The action may be a medical procedure, marketing cam…