no code implementations • 26 Sep 2023 • Haobing Liu, Jianyu Ding, Yanmin Zhu, Feilong Tang, Jiadi Yu, Ruobing Jiang, Zhongwen Guo
To extract multi-aspect preferences from target behaviors, we propose a multi-aspect projection mechanism for generating multiple preference representations from multiple aspects.
no code implementations • 10 Nov 2022 • Meng Chen, Li Lu, Jiadi Yu, Yingying Chen, Zhongjie Ba, Feng Lin, Kui Ren
In this paper, we propose a voice de-identification system, which uses adversarial examples to balance the privacy and utility of voice services.
no code implementations • 24 Jul 2022 • Haobing Liu, Yanmin Zhu, Chunyang Wang, Jianyu Ding, Jiadi Yu, Feilong Tang
An unsupervised way to construct a social behavior graph based on spatio-temporal data and to model social influences is proposed.
no code implementations • 9 Jun 2022 • Chunyang Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Jiadi Yu, Feilong Tang
For each recommendation scenario, we further discuss technical details about how existing methods apply meta-learning to improve the generalization ability of recommendation models.
no code implementations • 7 Aug 2021 • Tianzi Zang, Yanmin Zhu, Haobing Liu, Ruohan Zhang, Jiadi Yu
In this survey paper, we first proposed a two-level taxonomy of cross-domain recommendation which classifies different recommendation scenarios and recommendation tasks.
no code implementations • 25 Mar 2021 • Haobing Liu, Yanmin Zhu, Tianzi Zang, Yanan Xu, Jiadi Yu, Feilong Tang
In this paper, we focus on modeling heterogeneous behaviors and making multiple predictions together, since some prediction tasks are related and learning the model for a specific task may have the data sparsity problem.