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stat.ME2026
Causal Influence Maximization with Steady-State Guarantees
Renjie Cao, Zhuoxin Yan, Xinyan Su +1
Influence maximization in networks is a central problem in machine learning and causal inference, where an intervention on a subset of individuals triggers a diffusion process thro…
stat.ME2026
Budgeted Active Experimentation for Treatment Effect Estimation from Observational and Randomized Data
Jiacan Gao, Xinyan Su, Mingyuan Ma +7
Estimating heterogeneous treatment effects is central to data-driven decision-making, yet industrial applications often face a fundamental tension between limited randomized contro…
stat.ME2026
Orthogonal Uplift Learning with Permutation-Invariant Representations for Combinatorial Treatments
Xinyan Su, Jiacan Gao, Mingyuan Ma +6
We study uplift estimation for combinatorial treatments. Uplift measures the pure incremental causal effect of an intervention (e.g., sending a coupon or a marketing message) on us…