19 citations · 33 across the 11 of their papers we have counts for
5 papers · 1 filter
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles
Shengcai Liu, Fu Peng, Ke Tang
Attack Ensemble (AE), which combines multiple attacks together, provides a reliable way to evaluate adversarial robustness. In practice, AEs are often constructed and tuned by huma…
Disentangled Contrastive Learning for Social Recommendation
Jiahao Wu, Wenqi Fan, Jingfan Chen +3
Social recommendations utilize social relations to enhance the representation learning for recommendations. Most social recommendation models unify user representations for the use…
GANDSE: Generative Adversarial Network based Design Space Exploration for Neural Network Accelerator Design
Lang Feng, Wenjian Liu, Chuliang Guo +3
With the popularity of deep learning, the hardware implementation platform of deep learning has received increasing interest. Unlike the general purpose devices, e.g., CPU, or GPU,…
Defending Adversarial Examples by Negative Correlation Ensemble
Wenjian Luo, Hongwei Zhang, Linghao Kong +2
The security issues in DNNs, such as adversarial examples, have attracted much attention. Adversarial examples refer to the examples which are capable to induce the DNNs return com…
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack
Zeyu Dai, Shengcai Liu, Ke Tang +1
Deep neural networks are vulnerable to adversarial examples, even in the black-box setting where the attacker is only accessible to the model output. Recent studies have devised ef…