Digital technologies (e.g., mobile phones) can be used to obtain objective, frequent, and real-world digital phenotypes from individuals. However, modeling these data poses substantial challenges s…
Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the random partition based minibatch gradient descen…
The reduced-rank regression model is a popular model to deal with multivariate response and multiple predictors, and is widely used in biology, chemometrics, econometrics, engineering, and other fi…
Problem definition: Smart contract improves the supply chain efficiency by enabling the supplier’s commitment to postshipment financing decisions, which mitigates the bank’s lending risk exposu…
Modeling and inference for heterogeneous data have gained great interest recently due to rapid developments in personalized marketing. Most existing regression approaches are based on the condition…
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 …
Motivated by a product warranty claims dataset, we propose clustered coefficient regression models in a nonhomogeneous Poisson process for recurrent event data. The proposed method, referred as CLU…
Developing a confidence interval for the ratio of two quantities is an important task in statistics because of its omnipresence in real world applications. For such a problem, the MOVER-R (method o…
Strong variational sufficiency is a newly proposed property, which turns out to be of great use in the convergence analysis of multiplier methods. However, what this property implies for nonpolyhed…
A ride-hailing platform is an app-based, two-sided platform that matches riders with vehicles via information technology (IT). In 2015, the Shanghai government introduced a policy to restrict taxi …