39 citations · 78 across the 10 of their papers we have counts for
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stat.ML2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso
Danru Xu, Erdun Gao, Wei Huang +3
Learning the underlying Bayesian Networks (BNs), represented by directed acyclic graphs (DAGs), of the concerned events from purely-observational data is a crucial part of evidenti…
cs.LG2022★ 4 cited
Enhancing Adversarial Training with Second-Order Statistics of Weights
Gaojie Jin, Xinping Yi, Wei Huang +2
Adversarial training has been shown to be one of the most effective approaches to improve the robustness of deep neural networks. It is formalized as a min-max optimization over mo…
cs.LG2022★ 1 cited
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
Wei Huang, Chunrui Liu, Yilan Chen +2
PAC-Bayesian is an analysis framework where the training error can be expressed as the weighted average of the hypotheses in the posterior distribution whilst incorporating the pri…