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cs.LG2023★ 3 cited
Data-Driven Estimation of Heterogeneous Treatment Effects
Christopher Tran, Keith Burghardt, Kristina Lerman +1
Estimating how a treatment affects different individuals, known as heterogeneous treatment effect estimation, is an important problem in empirical sciences. In the last few years,…
cs.LG2022
Zero-shot meta-learning for small-scale data from human subjects
Julie Jiang, Kristina Lerman, Emilio Ferrara
While developments in machine learning led to impressive performance gains on big data, many human subjects data are, in actuality, small and sparsely labeled. Existing methods app…