5 citations · 11 across the 7 of their papers we have counts for
7 papers
On Rosenbaum's Rank-based Matching Estimator
Matias D. Cattaneo, Fang Han, Zhexiao Lin
In two influential contributions, Rosenbaum (2005, 2020) advocated for using the distances between component-wise ranks, instead of the original data values, to measure covariate s…
On the failure of the bootstrap for Chatterjee's rank correlation
Zhexiao Lin, Fang Han
While researchers commonly use the bootstrap for statistical inference, many of us have realized that the standard bootstrap, in general, does not work for Chatterjee's rank correl…
On regression-adjusted imputation estimators of the average treatment effect
Zhexiao Lin, Fang Han
Imputing missing potential outcomes using an estimated regression function is a natural idea for estimating causal effects. In the literature, estimators that combine imputation an…
Limit theorems of Chatterjee's rank correlation
Zhexiao Lin, Fang Han
Establishing the limiting distribution of Chatterjee's rank correlation for a general, possibly non-independent, pair of random variables has been eagerly awaited by many. This pap…
Estimation based on nearest neighbor matching: from density ratio to average treatment effect
Zhexiao Lin, Peng Ding, Fang Han
Nearest neighbor (NN) matching as a tool to align data sampled from different groups is both conceptually natural and practically well-used. In a landmark paper, Abadie and Imbens…
On boosting the power of Chatterjee's rank correlation
Zhexiao Lin, Fang Han
Chatterjee (2021)'s ingenious approach to estimating a measure of dependence first proposed by Dette et al. (2013) based on simple rank statistics has quickly caught attention. Thi…
Topic-aware chatbot using Recurrent Neural Networks and Nonnegative Matrix Factorization
Yuchen Guo, Nicholas Hanoian, Zhexiao Lin +8
We propose a novel model for a topic-aware chatbot by combining the traditional Recurrent Neural Network (RNN) encoder-decoder model with a topic attention layer based on Nonnegati…