Na Mou

According to our database, Na Mou authored at least 5 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation.

Ziyang Liu, Chaokun Wang, Jingcao Xu, Cheng Wu, Kai Zheng, Yang Song, Na Mou, Kun Gai

CoRR, 2023

SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems.

Beichuan Zhang, Chenggen Sun, Jianchao Tan, Xinjun Cai, Jun Zhao, Mengqi Miao, Kang Yin, Chengru Song, Na Mou, Yang Song

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

CAN: Feature Co-Action Network for Click-Through Rate Prediction.

Weijie Bian, Kailun Wu, Lejian Ren, Qi Pi, Yujing Zhang, Can Xiao, Xiang-Rong Sheng, Yong-Nan Zhu, Zhangming Chan, Na Mou, Xinchen Luo, Shiming Xiang, Guorui Zhou, Xiaoqiang Zhu, Hongbo Deng

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

2020

CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction.

Guorui Zhou, Weijie Bian, Kailun Wu, Lejian Ren, Qi Pi, Yujing Zhang, Can Xiao, Xiang-Rong Sheng, Na Mou, Xinchen Luo, Chi Zhang, Xianjie Qiao, Shiming Xiang, Kun Gai, Xiaoqiang Zhu, Jian Xu

CoRR, 2020

2019

Deep Interest Evolution Network for Click-Through Rate Prediction.

Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019