3 citations · 5 across the 6 of their papers we have counts for
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cs.IR2021★ 3 cited
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…
cs.IR2021★ 1 cited
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…
cs.CV2021★ 1 cited
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…