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Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for
  Multi-Label Classification

Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for Multi-Label Classification

Neural Networks (NN), 2019
5 November 2019
Guoqiang Wu
Ruobing Zheng
Ying-jie Tian
Dalian Liu
ArXiv (abs)PDFHTML

Papers citing "Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for Multi-Label Classification"

10 / 10 papers shown
Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVM
Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVM
Yuqi Liu
Yan Zheng
AILaw
380
0
0
16 Feb 2025
Methods for Class-Imbalanced Learning with Support Vector Machines: A
  Review and an Empirical Evaluation
Methods for Class-Imbalanced Learning with Support Vector Machines: A Review and an Empirical Evaluation
Salim rezvani
Farhad Pourpanah
Chee Peng Lim
Q. M. Jonathan Wu
VLM
88
24
0
05 Jun 2024
Adaptive Multiscale Retinal Diagnosis: A Hybrid Trio-Model Approach for
  Comprehensive Fundus Multi-Disease Detection Leveraging Transfer Learning and
  Siamese Networks
Adaptive Multiscale Retinal Diagnosis: A Hybrid Trio-Model Approach for Comprehensive Fundus Multi-Disease Detection Leveraging Transfer Learning and Siamese Networks
Yavuz Selim Inan
137
3
0
28 May 2024
Explainable machine learning multi-label classification of Spanish legal
  judgements
Explainable machine learning multi-label classification of Spanish legal judgements
Francisco de Arriba-Pérez
Silvia García-Méndez
Francisco J. González Castaño
Jaime González-González
AILaw
202
23
0
27 May 2024
Exploiting Multi-Label Correlation in Label Distribution Learning
Exploiting Multi-Label Correlation in Label Distribution LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
Zhi Kou
59
17
0
03 Aug 2023
Minimal Learning Machine for Multi-Label Learning
Minimal Learning Machine for Multi-Label Learning
J. Hämäläinen
Amauri Souza
C. L. C. Mattos
João Gomes
T. Kärkkäinen
217
2
0
09 May 2023
Towards Understanding Generalization of Macro-AUC in Multi-label
  Learning
Towards Understanding Generalization of Macro-AUC in Multi-label LearningInternational Conference on Machine Learning (ICML), 2023
Guoqiang Wu
Chongxuan Li
Yilong Yin
AI4CE
192
7
0
09 May 2023
An Ensemble Learning Based Approach to Multi-label Power Text
  Classification for Fault-type Recognition
An Ensemble Learning Based Approach to Multi-label Power Text Classification for Fault-type Recognition
Xiaona Chen
Tanvir Ahmad
Yinglong Ma
75
0
0
13 Apr 2022
Rethinking and Reweighting the Univariate Losses for Multi-Label
  Ranking: Consistency and Generalization
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and GeneralizationNeural Information Processing Systems (NeurIPS), 2021
Guoqiang Wu
Chongxuan Li
Kun Xu
Jun Zhu
126
12
0
10 May 2021
Multi-label classification: do Hamming loss and subset accuracy really
  conflict with each other?
Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?Neural Information Processing Systems (NeurIPS), 2020
Guoqiang Wu
Jun Zhu
187
39
0
16 Nov 2020
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