Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations. Recent works are mainly part-d…
Factor modeling is an essential tool for exploring intrinsic dependence structures in financial and economic studies through the construction of common latent variables, including the famous Fama…
Stochastic algebraic Riccati equations, also known as rational algebraic Riccati equations, arising in linear-quadratic optimal control for stochastic linear time-invariant systems, were considered…
We have theoretically investigated the polarization-dependent ultrashort pulse amplification in erbium-doped fluoride fibers. The numerical model is based on the coupled generalized nonlinear Schr…
Hard thresholding rule is commonly adopted in feature screening procedures to screen out unimportant predictors for ultrahigh-dimensional data. However, different thresholds are required to adapt t…
This article proposes a novel differential evolution algorithm for solving constrained multimodal multiobjective optimization problems (CMMOPs), which may have multiple feasible Pareto-optimal solu…
Many mobile games adopt autobattle systems in which the major consideration of players is how to assemble strong teams. The automated team assembly (ATA) becomes a crucial issue from different stan…
As Deep Learning (DL) models grow larger and more complex, training jobs are increasingly distributed across multiple Computing Units (CU) such as GPUs and TPUs. Each CU processes a sub-part of the…
We develop a new class of distribution-free multiple testing rules for false discovery rate (FDR) control under general dependence. A key element in our proposal is a symmetrized data aggregation (…
Decomposition plays a significant role in cooperative coevolution (CC), which shows great potential in large-scale black-box optimization (LSBO). However, current learning-based decomposition algor…