3 papers
cs.LG2026
Branch and Bound for Relational Verification of Neural Networks
Kota Fukuda, Zhenya Zhang, Guanqin Zhang +1
Verification of neural networks against relational specifications, such as global robustness, is crucial for safety-critical applications of cyber-physical systems (CPS), given the…
cs.LG2026
Truncated Kernel Stochastic Gradient Descent with General Losses and Spherical Radial Basis Functions
Jinhui Bai, Andreas Christmann, Lei Shi
In this paper, we propose a novel kernel stochastic gradient descent (SGD) algorithm for large-scale supervised learning with general losses. Compared to traditional kernel SGD, ou…
cs.LG2025
Truncated Kernel Stochastic Gradient Descent on Spheres
Jinhui Bai, Lei Shi
Inspired by the structure of spherical harmonics, we propose the truncated kernel stochastic gradient descent (T-kernel SGD) algorithm with a least-square loss function for spheric…