3 papers
math.ST2026
On the Impossibility of Specification Testing of Interference Models Based on Exposure Mappings
Chao Gao, Christopher Harshaw, Fredrik Sävje +1
Researchers use interference models based on exposure mappings to facilitate estimation of causal effects in randomized experiments with interference. To test the veracity of such…
cs.LG2026
Toward Highly Efficient and Private Submodular Maximization via Matrix-Based Acceleration
Boyu Liu, Lianke Qin, Zhao Song +2
Submodular function maximization is a critical building block for diverse tasks, such as document summarization, sensor placement, and image segmentation. Yet its practical utility…
stat.ME2025
A General Design-Based Framework and Estimator for Randomized Experiments
Christopher Harshaw, Fredrik Sävje, Yitan Wang
We describe a design-based framework for drawing causal inference in general randomized experiments. Causal effects are defined as linear functionals evaluated at unit-level potent…