Haibo Li

Automatic reproducing kernel and regularization for learning convolution kernels

2025 · arXiv (Cornell University)

Learning convolution kernels in operators from data arises in numerous applications and represents an ill-posed inverse problem of broad interest. With scant prior information, kernel methods offer a natural nonparametric approach with regularization. However, a …

RGCNet: Riemannian graph convolutional networks for end-to-end smart contract vulnerability detection

2026 · Neurocomputing

Frequent security issues with smart contract vulnerabilities have become a pressing challenge in the industry. Conventional program analysis methods lack flexibility and extensibility, leading to high false positive rates. Deep learning approaches are emerging as …