2 papers
cs.LG2024
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning
Pengfei Shi, Wei Zhong, Xinyu Zhang +4
Estimating the conditional average treatment effects (CATE) is very important in causal inference and has a wide range of applications across many fields. In the estimation process…
cs.LG2024
Ultra-imbalanced classification guided by statistical information
Yin Jin, Ningtao Wang, Ruofan Wu +3
Imbalanced data are frequently encountered in real-world classification tasks. Previous works on imbalanced learning mostly focused on learning with a minority class of few samples…