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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Multiple kernel learning for label relation and class imbalance in multi-label learning
Mingjing Han, Han Zhang
Information Sciences (2022) Vol. 613, pp. 344-356
Closed Access | Times Cited: 18

Showing 18 citing articles:

Semi-supervised imbalanced multi-label classification with label propagation
Guodong Du, Jia Zhang, Ning Zhang, et al.
Pattern Recognition (2024) Vol. 150, pp. 110358-110358
Closed Access | Times Cited: 16
Machine Learning-Assisted High-Throughput Screening for Electrocatalytic Hydrogen Evolution Reaction
Geng Yin, Haiyan Zhu, Shanlin Chen, et al.
Molecules (2025) Vol. 30, Iss. 4, pp. 759-759
Open Access
Power Load Forecasting System of Iron and Steel Enterprises Based on Deep Kernel–Multiple Kernel Joint Learning
Yan Zhang, Junsheng Wang, Jie Sun, et al.
Processes (2025) Vol. 13, Iss. 2, pp. 584-584
Open Access
Multi-label borderline oversampling technique
Zeyu Teng, Peng Cao, Min Huang, et al.
Pattern Recognition (2023) Vol. 145, pp. 109953-109953
Closed Access | Times Cited: 14
A Multi-Dimensional Feature Fusion Recognition Method for Space Infrared Dim Targets Based on Fuzzy Comprehensive with Spatio-Temporal Correlation
Shenghao Zhang, Peng Rao, Tingliang Hu, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 343-343
Open Access | Times Cited: 4
Theoretical Calculation Assisted by Machine Learning Accelerate Optimal Electrocatalyst Finding for Hydrogen Evolution Reaction
Yue‐Fei Zhang, Xuefei Liu, Wentao Wang
ChemElectroChem (2024) Vol. 11, Iss. 13
Open Access | Times Cited: 3
Oversampling multi-label data based on natural neighbor and label correlation
Bin Liu, Ao Zhou, Bingkun Wei, et al.
Expert Systems with Applications (2024) Vol. 259, pp. 125257-125257
Closed Access | Times Cited: 3
Partial random under/oversampling for multilabel problems
Nicolás García‐Pedrajas
Knowledge-Based Systems (2024) Vol. 302, pp. 112355-112355
Open Access | Times Cited: 2
Evolutionary simultaneous under and oversampling of instances for dealing with class-imbalance datasets in multilabel problems
Nicolás García‐Pedrajas, José M. Cuevas-Muñoz, Aida de Haro-García
Applied Soft Computing (2024) Vol. 159, pp. 111618-111618
Open Access | Times Cited: 2
Multi-label classification with weak labels by learning label correlation and label regularization
Xiaowan Ji, Anhui Tan, Wei-Zhi Wu, et al.
Applied Intelligence (2023) Vol. 53, Iss. 17, pp. 20110-20133
Closed Access | Times Cited: 5
Transformed Schatten-1 penalty based full-rank latent label learning for incomplete multi-label classification
Tingquan Deng, Qingwei Jia, Jingyu Wang, et al.
Information Sciences (2023) Vol. 650, pp. 119699-119699
Closed Access | Times Cited: 5
Deep self-organizing cube: A novel multi-dimensional classifier for multiple output learning
Ahmed Abdelfattah Saleh, Li Weigang
Expert Systems with Applications (2023) Vol. 230, pp. 120627-120627
Closed Access | Times Cited: 4
Multi-dimensional deep dense residual networks and multiple kernel learning for hyperspectral image classification
Huanhuan Lv, Ying Li, Hui Zhang, et al.
Infrared Physics & Technology (2024) Vol. 138, pp. 105265-105265
Closed Access | Times Cited: 1
Mixed structure low-rank representation for multi-view subspace clustering
Shouhang Wang, Yong Wang, Gui‐Fu Lu, et al.
Applied Intelligence (2023) Vol. 53, Iss. 15, pp. 18470-18487
Closed Access | Times Cited: 4
Learning local graph from multiple kernels
Zheng Liu, Shiluo Huang, Wei Jin, et al.
Neurocomputing (2023) Vol. 556, pp. 126683-126683
Closed Access | Times Cited: 3
E-SMOTE: Entropy Based Minority Oversampling for Heart Failure and AIDS Clinical Trails Analysis
Sainath Veerla, Anbu Valluvan Devadasan, Mohammad Masum, et al.
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC) (2024), pp. 1841-1846
Closed Access
A Multi-Output Regression Model for Energy Consumption Prediction Based on Optimized Multi-Kernel Learning: A Case Study of Tin Smelting Process
Zhenglang Wang, Zao Feng, Zhaojun Ma, et al.
Processes (2023) Vol. 12, Iss. 1, pp. 32-32
Open Access | Times Cited: 1
Oversampling Multi-Label Data Based on Natural Neighbor and Label Correlation
Bin Liu, Ao Zhou, Jin Wang, et al.
(2023)
Closed Access
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