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KMLP: A Scalable Hybrid Architecture for Web-Scale Tabular Data Modeling
Mingming Zhang, Pengfei Shi, Zhiqing Xiao +8
Predictive modeling on web-scale tabular data with billions of instances and hundreds of heterogeneous numerical features faces significant scalability challenges. These features e…
Beyond Tree Models: A Hybrid Model of KAN and gMLP for Large-Scale Financial Tabular Data
Mingming Zhang, Jiahao Hu, Pengfei Shi +8
Tabular data plays a critical role in real-world financial scenarios. Traditionally, tree models have dominated in handling tabular data. However, financial datasets in the industr…
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…
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…