Neural Supervised Clustering for Learning Individualized Treatment Rules with Many Treatments
Learning an individualized treatment rule (ITR) with many treatments requires estimating treatment-specific effects from limited observations per arm. Treatments with similar conditional responses can share information, but linear contrast models may miss nonlinear heterogeneity. We propose nonlinear supervised cluster...
Da-Xin Huang, Yi-Xin Yuan, Yi-Fan Dai et al.
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