55 citations · 69 across the 15 of their papers we have counts for
4 papers · 1 filter
Weight Expansion: A New Perspective on Dropout and Generalization
Gaojie Jin, Xinping Yi, Pengfei Yang +3
While dropout is known to be a successful regularization technique, insights into the mechanisms that lead to this success are still lacking. We introduce the concept of \emph{weig…
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness
Renjue Li, Hanwei Zhang, Pengfei Yang +4
In this paper, we propose a framework of filter-based ensemble of deep neuralnetworks (DNNs) to defend against adversarial attacks. The framework builds an ensemble of sub-models -…
Towards Practical Robustness Analysis for DNNs based on PAC-Model Learning
Renjue Li, Pengfei Yang, Cheng-Chao Huang +3
To analyse local robustness properties of deep neural networks (DNNs), we present a practical framework from a model learning perspective. Based on black-box model learning with sc…
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification
Jianlin Li, Pengfei Yang, Jiangchao Liu +3
Deep neural networks (DNNs) have been shown lack of robustness for the vulnerability of their classification to small perturbations on the inputs. This has led to safety concerns o…