<b>COLTR</b>: Semi-Supervised Learning to Rank With Co-Training and Over-Parameterization for Web Search-Reference-Cited by-同舟云学术

COLTR: Semi-Supervised Learning to Rank With Co-Training and Over-Parameterization for Web Search

Published:2023-12-01 Issue:12 Volume:35 Page:12542-12555
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Li Yuchen¹^ORCID,Xiong Haoyi²^ORCID,Wang Qingzhong²^ORCID,Kong Linghe¹^ORCID,Liu Hao³^ORCID,Li Haifang²^ORCID,Bian Jiang²^ORCID,Wang Shuaiqiang²^ORCID,Chen Guihai¹^ORCID,Dou Dejing²^ORCID,Yin Dawei²^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

2. Baidu, Inc., Beijing, China

3. Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong Province, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Shanghai Institutions of Higher Learning

Shanghai Science and Technology Development Funds

Zhejiang Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/10311056/10109140.pdf?arnumber=10109140

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