no code implementations • 4 Jul 2023 • Wei zhang, Ping Zhang, Jian Dong, Yongkang Wang, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang
The effectiveness of ad creatives is greatly influenced by their visual appearance.
no code implementations • 26 Jun 2023 • Wei zhang, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang
The disadvantage of the former is that the data from other domains is not utilized by a single domain model, while the latter leverage all the data from different domains, but the fine-tuned model of transfer learning may trap the model in a local optimum of the source domain, making it difficult to fit the target domain.
no code implementations • 5 Jun 2023 • Huinan Sun, Guangliang Yu, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang
It consists of a multi-interest graph structure for capturing long-term user behavior, a multi-scenario heterogeneous sequence model for modeling short-term information, then an adaptive fusion mechanism to fused information from long-term and short-term behaviors.
no code implementations • 17 Jun 2020 • Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai
These stages usually allocate resource manually with specific computing power budgets, which requires the serving configuration to adapt accordingly.
1 code implementation • NeurIPS 2019 • Han Zhu, Daqing Chang, Ziru Xu, Pengye Zhang, Xiang Li, Jie He, Han Li, Jian Xu, Kun Gai
The previous work Tree-based Deep Model (TDM) \cite{zhu2018learning} greatly improves recommendation accuracy using tree index.
4 code implementations • 8 Jan 2018 • Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai
In systems with large corpus, however, the calculation cost for the learnt model to predict all user-item preferences is tremendous, which makes full corpus retrieval extremely difficult.