Multi-Scale User Behavior Network for Entire Space Multi-Task Learning-Reference-Cited by-同舟云学术

Multi-Scale User Behavior Network for Entire Space Multi-Task Learning

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Jin Jiarui¹,Chen Xianyu¹,Zhang Weinan¹,Chen Yuanbo²,Jiang Zaifan²,Zhu Zekun²,Su Zhewen²,Yu Yong¹

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Alibaba Group, Beijing, China

Funder

National Natural Science Foundation of China

Shanghai Municipal Science and Technology Major Project

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557405

Reference34 articles.

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4. Xin Dai Xiangnan Kong Tian Guo and Xinlu He. 2021. FiShNet: Fine-Grained Filter Sharing for Resource-Efficient Multi-Task Learning. In CIKM. Xin Dai Xiangnan Kong Tian Guo and Xinlu He. 2021. FiShNet: Fine-Grained Filter Sharing for Resource-Efficient Multi-Task Learning. In CIKM.

5. Ke Ding Xin Dong Yong He Lei Cheng Chilin Fu Zhaoxin Huan Hai Li Tan Yan Liang Zhang Xiaolu Zhang etal 2021. MSSM: a multiple-level sparse sharing model for efficient multi-task learning. In SIGIR. Ke Ding Xin Dong Yong He Lei Cheng Chilin Fu Zhaoxin Huan Hai Li Tan Yan Liang Zhang Xiaolu Zhang et al. 2021. MSSM: a multiple-level sparse sharing model for efficient multi-task learning. In SIGIR.

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