We propose a unified game-theoretical framework to perform classification and conditional image generation given limited supervision. It is formulated as a three-player minimax game consisting of a…
Modern statistical analysis often encounters massive datasets with ultrahigh-dimensional features. In this work, we develop a subsampling approach for feature screening with massive datasets. The a…
We propose a new asset pricing model that is applicable to the big panel of return data. The main idea of this model is to learn the conditional distribution of the return, which is approximated by…
Vector autoregression model is ubiquitous in classical time series data analysis. With the rapid advance of social network sites, time series data over latent graph is becoming increasingly popular…
This article introduces an Ordinary Differential Equation (ODE) notion for survival analysis. The ODE notion not only provides a unified modeling framework, but more importantly, also enables the d…
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…
This article proposes a nonparametric projection-based adaptive-to-model specification test for regressions with discrete and continuous predictors. The test statistic is asymptotically normal unde…
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 …
In this article, we test for the effects of high-dimensional covariates on the response. In many applications, different components of covariates usually exhibit various levels of variation, which …
Evolutionary multitasking (EMT) is one of the emerging topics in evolutionary computation. EMT can solve multiple related optimization tasks simultaneously and enhance the optimization of each task…