Generalized Additive Partial Linear Models (GAPLMs) are appealing for model interpretation and prediction. However, for GAPLMs, the covariates and the degree of smoothing in the nonparametric parts…
Randomized block factorial experiments are widely used in industrial engineering, clinical trials, and social science. Researchers often use a linear model and analysis of covariance to analyze exp…
Topic models provide a useful text-mining tool for learning, extracting, and discovering latent structures in large text corpora. Although a plethora of methods have been proposed for topic modelin…
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 …
In this paper, we present a first-order projection-free method, namely, the universal conditional gradient sliding (UCGS) method, for computing -approximate solutions to convex differentiable optim…
Owing to the mutual orthogonality among different orbital angular momentums (OAM), OAM mode has been considered as a promising candidate for improving channel capacity and spectrum efficiency. Howe…
One fundamental problem in constrained decentralized multiagent optimization is the trade-off between gradient/sampling complexity and communication complexity. In this paper, we propose new algori…
The compensation for in-phase/quadrature (IQ) and polarization imbalance residing at the coherent transceivers is crucial to the overall performance of high-speed transmission systems. To simultane…
In recent years, many nontraditional classification methods, such as random forest, boosting, and neural network, have been widely used in applications. Their performance is typically measured in t…