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stat.ML2025
Universal rates of ERM for agnostic learning
Steve Hanneke, Mingyue Xu
The universal learning framework has been developed to obtain guarantees on the learning rates that hold for any fixed distribution, which can be much faster than the ones uniforml…
cs.CV2025
Rethinking Gradient-based Adversarial Attacks on Point Cloud Classification
Jun Chen, Xinke Li, Mingyue Xu +2
Gradient-based adversarial attacks are widely used to evaluate the robustness of 3D point cloud classifiers, yet they often rely on uniform update rules that neglect point-wise het…
stat.ML2025
Universal Rates of Empirical Risk Minimization
Steve Hanneke, Mingyue Xu
The well-known empirical risk minimization (ERM) principle is the basis of many widely used machine learning algorithms, and plays an essential role in the classical PAC theory. A…