Outlier-Robust Feature Selection with ℓ<sub>2,1</sub>-Norm Minimization and Group Row-Sparsity Induced Constraints-Reference-Cited by-同舟云学术

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Outlier-Robust Feature Selection with ℓ_2,1-Norm Minimization and Group Row-Sparsity Induced Constraints

Published:2024-04-14 Issue: Volume:23 Page:3585-3589
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Wang Jie¹,Wang Zheng¹,Wang Rong¹,Nie Feiping¹,Li Xuelong¹

Affiliation:

1. Northwestern Polytechnical University,School of Artificial Intelligence, OPtics and ElectroNics (iOPEN),Xi’ an,P. R. China,710072

Funder

National Key Research and Development Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447418.pdf?arnumber=10447418

Reference20 articles.

1. Neural Speech Phase Prediction Based on Parallel Estimation Architecture and Anti-Wrapping Losses

2. Unsupervised Feature Selection With Weighted and Projected Adaptive Neighbors

3. Group-Wise Feature Selection for Supervised Learning

4. Optimum Feature Ordering for Dynamic Instance–Wise Joint Feature Selection and Classification

5. Efficient and robust feature selection via joint 2, 1-norms minimization;Nie;Advances in neural information processing systems,2010

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