no code implementations • 22 Dec 2017 • Kui Zhao, Yuechuan Li, Zhaoqian Shuai, Cheng Yang
Many machine intelligence techniques are developed in E-commerce and one of the most essential components is the representation of IDs, including user ID, item ID, product ID, store ID, brand ID, category ID etc.
no code implementations • 24 Jan 2018 • Kui Zhao, Yuechuan Li, Chi Zhang, Cheng Yang, Huan Xu
By leveraging the mixture layer, the proposed method can adaptively update states according to the similarities between encoded inputs and prototype vectors, leading to a stronger capacity in assimilating sequences with multiple patterns.
no code implementations • 26 Aug 2017 • Kui Zhao, Can Wang
To overcome the limitations of existing methods, we propose a novel approach in this paper to learn effective features automatically from the structured data using the Convolutional Neural Network (CNN).
no code implementations • 26 Aug 2017 • Kui Zhao, Bangpeng Li, Zilun Peng, Jiajun Bu, Can Wang
Dynamic and personalized elements such as top stories, recommended list in a webpage are vital to the understanding of the dynamic nature of web 2. 0 sites.
no code implementations • 26 Aug 2017 • Kui Zhao, Xia Hu, Jiajun Bu, Can Wang
In order to answer these kinds of questions, we attempt to model human sense of style compatibility in this paper.
no code implementations • 4 Feb 2019 • Kui Zhao, Junhao Hua, Ling Yan, Qi Zhang, Huan Xu, Cheng Yang
In our approach, a semi-black-box model is built to forecast the dynamic market response and an efficient optimization method is proposed to solve the complex allocation task.
no code implementations • 2 May 2020 • Zebang Zhang, Kui Zhao, Kai Huang, Quanhui Jia, Yanming Fang, Quan Yu
If the uncertainty of an enterprise's revenue forecasting can be estimated, a more proper credit limit can be granted.
no code implementations • 10 Jul 2020 • Hang Miao, Kui Zhao, Zhun Wang, Linbo Jiang, Quanhui Jia, Yanming Fang, Quan Yu
Based on these testing data, a response model is then built to measure the heterogeneous treatment effect of increasing credit limits (i. e. treatments) for different customers, who are depicted by several control variables (i. e. features).