23 citations · 29 across the 3 of their papers we have counts for
3 papers
cs.LG2017★ 5 cited
A Practically Competitive and Provably Consistent Algorithm for Uplift Modeling
Yan Zhao, Xiao Fang, David Simchi-Levi
Randomized experiments have been critical tools of decision making for decades. However, subjects can show significant heterogeneity in response to treatments in many important app…
cs.AI2017★ 1 cited
Uplift Modeling with Multiple Treatments and General Response Types
Yan Zhao, Xiao Fang, David Simchi-Levi
Randomized experiments have been used to assist decision-making in many areas. They help people select the optimal treatment for the test population with certain statistical guaran…
stat.ME2008★ 23 cited
Locally D-optimal designs based on a class of composed models resulted from blending Emax and one-compartment models
X. Fang, A. S. Hedayat
A class of nonlinear models combining a pharmacokinetic compartmental model and a pharmacodynamic Emax model is introduced. The locally D-optimal (LD) design for a four-parameter c…