Robust Supervised and Semisupervised Least Squares Regression Using ℓ $$_{2,p}$ -Norm Minimization-Reference-Cited by-同舟云学术

Robust Supervised and Semisupervised Least Squares Regression Using ℓ $$_{2,p}$ -Norm Minimization

Published:2023 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Wang Jingyu¹^ORCID,Xie Fangyuan²^ORCID,Nie Feiping³^ORCID,Li Xuelong³^ORCID

Affiliation:

1. School of Astronautics, School of Artificial Intelligence, OPtics and ElectroNics, Northwestern Polytechnical University, Xi'an 710072, China.

2. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China.

3. School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi'an 710072, China, and also with the Key Laboratory of Intelligent Interaction and Applications, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an 710072, China.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Innovation Capability Support Program of Shaanxi

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/09718600.pdf?arnumber=9718600

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