no code implementations • 26 Dec 2023 • Chen Yang, Jin Chen, Qian Yu, Xiangdong Wu, Kui Ma, Zihao Zhao, Zhiwei Fang, Wenlong Chen, Chaosheng Fan, Jie He, Changping Peng, Zhangang Lin, Jingping Shao
To address the aforementioned issue, we propose an incremental update framework for online recommenders with Data-Driven Prior (DDP), which is composed of Feature Prior (FP) and Model Prior (MP).
1 code implementation • 12 Oct 2023 • Jinbo Song, Ruoran Huang, Xinyang Wang, Wei Huang, Qian Yu, Mingming Chen, Yafei Yao, Chaosheng Fan, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao
Industrial systems such as recommender systems and online advertising, have been widely equipped with multi-stage architectures, which are divided into several cascaded modules, including matching, pre-ranking, ranking and re-ranking.
no code implementations • 17 Jan 2022 • Xiaoxiao Xu, Chen Yang, Qian Yu, Zhiwei Fang, Jiaxing Wang, Chaosheng Fan, Yang He, Changping Peng, Zhangang Lin, Jingping Shao
We propose a general Variational Embedding Learning Framework (VELF) for alleviating the severe cold-start problem in CTR prediction.
no code implementations • 22 Aug 2020 • Xuanji Xiao, Hua-Bin Chen, Yuzhen Liu, Xing Yao, Pei Liu, Chaosheng Fan, Nian Ji, Xirong Jiang
To address this sharing&conflict problem, we propose a novel multi-task CVR modeling scheme with neuron-connection level sharing named NCS4CVR, which can automatically and flexibly learn which neuron weights are shared or not shared without artificial experience.