no code implementations • 15 Mar 2024 • Yuanbo Gao, Peng Lin, Dongyue Wang, Feng Mei, Xiwei Zhao, Sulong Xu, Jinghe Hu
However, the explosive growth of online latency can be attributed to the huge parameters in the pre-trained model.
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 Apr 2023 • Congcong Liu, Fei Teng, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao
Streaming data has the characteristic that the underlying distribution drifts over time and may recur.
1 code implementation • 5 Dec 2022 • Xi Zhao, Wei Feng, Zheng Zhang, Jingjing Lv, Xin Zhu, Zhangang Lin, Jinghe Hu, Jingping Shao
Recently, segmentation-based methods are quite popular in scene text detection, which mainly contain two steps: text kernel segmentation and expansion.
no code implementations • 26 Jun 2022 • Han Xu, Hao Qi, Kunyao Wang, Pei Wang, Guowei Zhang, Congcong Liu, Junsheng Jin, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao
In this work, we propose a novel framework PCDF(Parallel-Computing Distributed Framework), allowing to split the computation cost into three parts and to deploy them in the pre-module in parallel with the retrieval stage, the middle-module for ranking ads, and the post-module for re-ranking ads with external items.
no code implementations • 1 Apr 2022 • Congcong Liu, Yuejiang Li, Fei Teng, Xiwei Zhao, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao
Click-through rate (CTR) prediction is a crucial task in web search, recommender systems, and online advertisement displaying.
no code implementations • 1 Sep 2017 • Yu Wang, Jixing Xu, Aohan Wu, Mantian Li, Yang He, Jinghe Hu, Weipeng P. Yan
This paper proposes Telepath, a vision-based bionic recommender system model, which understands users from such perspective.
no code implementations • 18 Aug 2017 • Yu Wang, Jiayi Liu, Yuxiang Liu, Jun Hao, Yang He, Jinghe Hu, Weipeng P. Yan, Mantian Li
We present LADDER, the first deep reinforcement learning agent that can successfully learn control policies for large-scale real-world problems directly from raw inputs composed of high-level semantic information.
no code implementations • 14 Aug 2017 • Yan Yan, Wentao Guo, Meng Zhao, Jinghe Hu, Weipeng P. Yan
With the transition from people's traditional `brick-and-mortar' shopping to online mobile shopping patterns in web 2. 0 $\mathit{era}$, the recommender system plays a critical role in E-Commerce and E-Retails.