3 citations · 5 across the 6 of their papers we have counts for
6 papers
Towards Robust Recommendation: A Review and an Adversarial Robustness Evaluation Library
Lei Cheng, Xiaowen Huang, Jitao Sang +1
Recently, recommender system has achieved significant success. However, due to the openness of recommender systems, they remain vulnerable to malicious attacks. Additionally, natur…
Learning to Learn a Cold-start Sequential Recommender
Xiaowen Huang, Jitao Sang, Jian Yu +1
The cold-start recommendation is an urgent problem in contemporary online applications. It aims to provide users whose behaviors are literally sparse with as accurate recommendatio…
Knowledge Graph-enhanced Sampling for Conversational Recommender System
Mengyuan Zhao, Xiaowen Huang, Lixi Zhu +2
The traditional recommendation systems mainly use offline user data to train offline models, and then recommend items for online users, thus suffering from the unreliable estimatio…
ImageNet Pre-training also Transfers Non-Robustness
Jiaming Zhang, Jitao Sang, Qi Yi +3
ImageNet pre-training has enabled state-of-the-art results on many tasks. In spite of its recognized contribution to generalization, we observed in this study that ImageNet pre-tra…
A Generalization Theory based on Independent and Task-Identically Distributed Assumption
Guanhua Zheng, Jitao Sang, Houqiang Li +2
Existing generalization theories analyze the generalization performance mainly based on the model complexity and training process. The ignorance of the task properties, which resul…
Attention, Please! Adversarial Defense via Activation Rectification and Preservation
Shangxi Wu, Jitao Sang, Kaiyuan Xu +2
This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change. In particular, we obs…