1 code implementation • CVPR 2023 • Kun Yan, Xiao Li, Fangyun Wei, Jinglu Wang, Chenbin Zhang, Ping Wang, Yan Lu
The underlying idea is to generate pseudo labels for unlabeled frames during training and to optimize the model on the combination of labeled and pseudo-labeled data.
no code implementations • 5 Feb 2023 • Jianxin Chang, Chenbin Zhang, Zhiyi Fu, Xiaoxue Zang, Lin Guan, Jing Lu, Yiqun Hui, Dewei Leng, Yanan Niu, Yang song, Kun Gai
And for the user-item cross features, we compress each into a one-dimentional bias term in the attention score calculation to save the computational cost.
1 code implementation • 2 Feb 2023 • Jianxin Chang, Chenbin Zhang, Yiqun Hui, Dewei Leng, Yanan Niu, Yang song, Kun Gai
By infusing personalized selection of Embedding and personalized modification of DNN parameters, PEPNet tailored to the interests of each individual obtains significant performance gains, with online improvements exceeding 1\% in multiple task metrics across multiple domains.
no code implementations • 2 Dec 2021 • Kun Yan, Chenbin Zhang, Jun Hou, Ping Wang, Zied Bouraoui, Shoaib Jameel, Steven Schockaert
A key feature of the multi-label setting is that images often have multiple labels, which typically refer to different regions of the image.
no code implementations • 9 Oct 2019 • Hong Yu, Xiaofan Zhang, Lingjun Song, Liren Jiang, Xiaodi Huang, Wen Chen, Chenbin Zhang, Jiahui Li, Jiji Yang, Zhiqiang Hu, Qi Duan, Wanyuan Chen, Xianglei He, Jinshuang Fan, Weihai Jiang, Li Zhang, Chengmin Qiu, Minmin Gu, Weiwei Sun, Yangqiong Zhang, Guangyin Peng, Weiwei Shen, Guohui Fu
Gastric cancer is one of the most common cancers, which ranks third among the leading causes of cancer death.
1 code implementation • ACL 2019 • Junyu Lu, Chenbin Zhang, Zeying Xie, Guang Ling, Tom Chao Zhou, Zenglin Xu
Response selection plays an important role in fully automated dialogue systems.
1 code implementation • CVPR 2019 • Jian Liang, Yuren Cao, Chenbin Zhang, Shiyu Chang, Kun Bai, Zenglin Xu
Authentication is a task aiming to confirm the truth between data instances and personal identities.