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Na Mou

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Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems

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May 08, 2024
Kai Zheng, Haijun Zhao, Rui Huang, Beichuan Zhang, Na Mou, Yanan Niu, Yang Song, Hongning Wang, Kun Gai

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End-to-end training of Multimodal Model and ranking Model

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Apr 09, 2024
Xiuqi Deng, Lu Xu, Xiyao Li, Jinkai Yu, Erpeng Xue, Zhongyuan Wang, Di Zhang, Zhaojie Liu, Guorui Zhou, Yang Song, Na Mou, Shen Jiang, Han Li

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

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Aug 18, 2023
Beichuan Zhang, Chenggen Sun, Jianchao Tan, Xinjun Cai, Jun Zhao, Mengqi Miao, Kang Yin, Chengru Song, Na Mou, Yang Song

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

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Jun 08, 2023
Ziyang Liu, Chaokun Wang, Jingcao Xu, Cheng Wu, Kai Zheng, Yang Song, Na Mou, Kun Gai

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

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Nov 11, 2020
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

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Deep Interest Evolution Network for Click-Through Rate Prediction

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Nov 06, 2018
Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai

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