1 code implementation • 24 May 2023 • Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He
Through theoretical analyses, we identify two fundamental factors: (1) with graph convolution (\textit{i. e.,} neighborhood aggregation), popular items exert larger influence than tail items on neighbor users, making the users move towards popular items in the representation space; (2) after multiple times of graph convolution, popular items would affect more high-order neighbors and become more influential.
1 code implementation • 20 May 2022 • Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu
However, existing graph-based methods fails to consider the bias offsets of users (items).
no code implementations • 16 Dec 2021 • Xiaojie Guo, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu
In addition, this kind of product description should be eye-catching to the readers.
no code implementations • 15 Dec 2021 • Xueying Zhang, Yanyan Zou, Hainan Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu
It consists of two main components: 1) natural language generation, which is built from a transformer-pointer network and a pre-trained sequence-to-sequence model based on millions of training data from our in-house platform; and 2) copywriting quality control, which is based on both automatic evaluation and human screening.
no code implementations • 29 Oct 2020 • Jun Li, Lei Chen, Jiajia Chen
Two-step aggregation is introduced to facilitate scalable federated learning (SFL) over passive optical networks (PONs).
Networking and Internet Architecture
no code implementations • 24 Oct 2019 • Jun Li, Xiaoman Shen, Lei Chen, Jiajia Chen
Bandwidth slicing is introduced to support federated learning in edge computing to assure low communication delay for training traffic.
no code implementations • 21 Dec 2017 • Yingxiang Sun, Jiajia Chen, Chau Yuen, Susanto Rahardja
It is known that adverse environments such as high reverberation and low signal-to-noise ratio (SNR) pose a great challenge to indoor sound source localization.