This paper is concerned with causal mediation analysis with varying indirect and direct effects. We propose a varying coefficient mediation model, which can also be viewed as an extension of modera…
This paper reviews the novel concept of a controllable variational autoencoder (ControlVAE), discusses its parameter tuning to meet application needs, derives its key analytic properties, and offer…
Large-scale association analysis between multivariate responses and predictors is of great practical importance, as exemplified by modern business applications including social media marketing and …
Email marketing has been an increasingly important tool for today’s businesses. In this article, we propose a counting-process-based Bayesian method for quantifying the effectiveness of email mar…
Modern machine learning models often exhibit the benign overfitting phenomenon, which has recently been characterized using the double descent curves. In addition to the classical U-shaped learning…
Urban anomalies bring uncertainties to society, urban transportation systems, and businesses. Some urban anomalies, such as no-notice and/or unpredictable terrorist attacks or other urban strikes, …
We examine how social influence interacts with other information sources to affect user behaviors in the context of medical crowdfunding. We conduct a large-scale randomized field experiment on a l…
In the era of data science, it is common to encounter data with different subsets of variables obtained for different cases. An example is the split questionnaire design (SQD), which is adopted to …
Red micro light-emitting diodes (micro-LEDs) on silicon substrates are crucial for the realization of large-scale, high-quality, low-cost micro-LED displays, and are also beneficial for high-speed …
We propose and demonstrate a deep learning-assisted photonic approach for measuring the angle-of-arrival (AOA) with high-precision, which is suitable for long-baseline direction finding (DF). A non…