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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 9: AAAI-21 Technical Tracks 9

Self-Paced Two-dimensional PCA

February 1, 2023

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Authors

Jiangxin Li

University of Electronic Science and Technology of China


Zhao Kang

University of Electronic Science and Technology of China


Chong Peng

Qingdao University


Wenyu Chen

University of Electronic Science and Technology of China


DOI:

10.1609/aaai.v35i9.17020


Abstract:

Two-dimensional PCA (2DPCA) is an effective approach to reduce dimension and extract features in the image domain. Most recently developed techniques use different error measures to improve their robustness to outliers. When certain data points are overly contaminated, the existing methods are frequently incapable of filtering out and eliminating the excessively polluted ones. Moreover, natural systems have smooth dynamics, an opportunity is lost if an unsupervised objective function remains static. Unlike previous studies, we explicitly differentiate the samples to alleviate the impact of outliers and propose a novel method called Self-Paced 2DPCA (SP2DPCA)algorithm, which progresses from `easy’ to `complex’ samples. By using an alternative optimization strategy, SP2DPCA looks for optimal projection matrix and filters out outliers iteratively. Theoretical analysis demonstrates the robustness nature of our method. Extensive experiments on image reconstruction and clustering verify the superiority of our approach.

Topics: AAAI

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HOW TO CITE:

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen Self-Paced Two-dimensional PCA Proceedings of the AAAI Conference on Artificial Intelligence (2021) 8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen Self-Paced Two-dimensional PCA AAAI 2021, 8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen (2021). Self-Paced Two-dimensional PCA. Proceedings of the AAAI Conference on Artificial Intelligence, 8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen. Self-Paced Two-dimensional PCA. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen. 2021. Self-Paced Two-dimensional PCA. "Proceedings of the AAAI Conference on Artificial Intelligence". 8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen. (2021) "Self-Paced Two-dimensional PCA", Proceedings of the AAAI Conference on Artificial Intelligence, p.8392-8400

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen, "Self-Paced Two-dimensional PCA", AAAI, p.8392-8400, 2021.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen. "Self-Paced Two-dimensional PCA". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen. "Self-Paced Two-dimensional PCA". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 8392-8400.

Jiangxin Li||Zhao Kang||Chong Peng||Wenyu Chen. Self-Paced Two-dimensional PCA. AAAI[Internet]. 2021[cited 2023]; 8392-8400.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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