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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 27 / No. 1: Twenty-Seventh AAAI Conference on Artificial Intelligence

Multi-Label Learning with PRO Loss

March 8, 2023

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Authors

Miao Xu

Nanjing University


Yu-Feng Li

Nanjing University


Zhi-Hua Zhou

Nanjing University


DOI:

10.1609/aaai.v27i1.8689


Abstract:

Multi-label learning methods assign multiple labels to one object. In practice, in addition to differentiating relevant labels from irrelevant ones, it is often desired to rank the relevant labels for an object, whereas the rankings of irrelevant labels are not important. Such a requirement, however, cannot be met because most existing methods were designed to optimize existing criteria, yet there is no criterion which encodes the aforementioned requirement. In this paper, we present a new criterion, Pro Loss, concerning the prediction on all labels as well as the rankings of only relevant labels. We then propose ProSVM which optimizes Pro Lossefficiently using alternating direction method of multipliers. We further improve its efficiency with an upper approximation that reduces the number of constraints from O(T,2) to O(T), where T is the number of labels. Experiments show that our proposals are not only superior on Pro Loss, but also highly competitive on existing evaluation criteria.

Topics: AAAI

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HOW TO CITE:

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou Multi-Label Learning with PRO Loss Proceedings of the AAAI Conference on Artificial Intelligence, 27 (2013) 998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou Multi-Label Learning with PRO Loss AAAI 2013, 998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou (2013). Multi-Label Learning with PRO Loss. Proceedings of the AAAI Conference on Artificial Intelligence, 27, 998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou. Multi-Label Learning with PRO Loss. Proceedings of the AAAI Conference on Artificial Intelligence, 27 2013 p.998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou. 2013. Multi-Label Learning with PRO Loss. "Proceedings of the AAAI Conference on Artificial Intelligence, 27". 998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou. (2013) "Multi-Label Learning with PRO Loss", Proceedings of the AAAI Conference on Artificial Intelligence, 27, p.998

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou, "Multi-Label Learning with PRO Loss", AAAI, p.998, 2013.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou. "Multi-Label Learning with PRO Loss". Proceedings of the AAAI Conference on Artificial Intelligence, 27, 2013, p.998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou. "Multi-Label Learning with PRO Loss". Proceedings of the AAAI Conference on Artificial Intelligence, 27, (2013): 998.

Miao Xu|| Yu-Feng Li|| Zhi-Hua Zhou. Multi-Label Learning with PRO Loss. AAAI[Internet]. 2013[cited 2023]; 998.


ISSN: 2374-3468


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