155 citations · 259 across the 7 of their papers we have counts for
8 papers
Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness
Dazhong Shen, Chuan Qin, Chao Wang +3
As one of the most popular generative models, Variational Autoencoder (VAE) approximates the posterior of latent variables based on amortized variational inference. However, when t…
Adversarial Examples Detection beyond Image Space
Kejiang Chen, Yuefeng Chen, Hang Zhou +4
Deep neural networks have been proved that they are vulnerable to adversarial examples, which are generated by adding human-imperceptible perturbations to images. To defend these a…
Adam revisited: a weighted past gradients perspective
Hui Zhong, Zaiyi Chen, Chuan Qin +4
Adaptive learning rate methods have been successfully applied in many fields, especially in training deep neural networks. Recent results have shown that adaptive methods with expo…
GreedyFool: Distortion-Aware Sparse Adversarial Attack
Xiaoyi Dong, Dongdong Chen, Jianmin Bao +5
Modern deep neural networks(DNNs) are vulnerable to adversarial samples. Sparse adversarial samples are a special branch of adversarial samples that can fool the target model by on…
A Survey on Knowledge Graph-Based Recommender Systems
Qingyu Guo, Fuzhen Zhuang, Chuan Qin +4
To solve the information explosion problem and enhance user experience in various online applications, recommender systems have been developed to model users preferences. Although…
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback
Chao Wang, Hengshu Zhu, Chen Zhu +2
The recent development of online recommender systems has a focus on collaborative ranking from implicit feedback, such as user clicks and purchases. Different from explicit ratings…