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:

Non-convex feature selection based on feature correlation representation and dual manifold optimization
Ronghua Shang, Lizhuo Gao, Haijing Chi, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123867-123867
Closed Access | Times Cited: 7

Showing 7 citing articles:

Robust Multi-view Unsupervised Feature Selection via Latent Consensus Structure Learning
Chenxi Wang, Peng Song
Information Sciences (2025), pp. 122177-122177
Closed Access

Unsupervised feature selection with evolutionary sparsity
Shixuan Zhou, Yi Xiang, Han Huang, et al.
Neural Networks (2025) Vol. 189, pp. 107512-107512
Closed Access

Dual-dual subspace learning with low-rank consideration for feature selection
Amir Moslemi, Mahdi Bidar
Physica A Statistical Mechanics and its Applications (2024) Vol. 651, pp. 129997-129997
Closed Access | Times Cited: 2

BYDSEX: Binary Young's Double-Slit Experiment Optimizer with Adaptive Crossover for Feature Selection: Investigating Performance Issues of Network Intrusion Detection
Doaa El-Shahat, Mohamed Abdel‐Basset, Nourhan Talal, et al.
Knowledge-Based Systems (2024) Vol. 305, pp. 112589-112589
Closed Access | Times Cited: 2

Fuzzy feature factorization machine: Bridging feature interaction, selection, and construction
Qihang Guo, Keyu Liu, Taihua Xu, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124600-124600
Closed Access | Times Cited: 1

Double-dictionary learning unsupervised feature selection cooperating with low-rank and sparsity
Ronghua Shang, Jiuzheng Song, Lizhuo Gao, et al.
Knowledge-Based Systems (2024) Vol. 304, pp. 112566-112566
Closed Access | Times Cited: 1

Subspace learning using low-rank latent representation learning and perturbation theorem: Unsupervised gene selection
Amir Moslemi, Fariborz Baghaei Naeini
Computers in Biology and Medicine (2024) Vol. 185, pp. 109567-109567
Closed Access

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