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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:

Robust non-convex least squares loss function for regression with outliers
Kuaini Wang, Ping Zhong
Knowledge-Based Systems (2014) Vol. 71, pp. 290-302
Closed Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Low-rank local tangent space embedding for subspace clustering
Tingquan Deng, Dongsheng Ye, Rong Ma, et al.
Information Sciences (2019) Vol. 508, pp. 1-21
Closed Access | Times Cited: 104
Maximum likelihood optimal and robust Support Vector Regression with lncosh loss function
Ömer Karal
Neural Networks (2017) Vol. 94, pp. 1-12
Closed Access | Times Cited: 66
Robust functional regression for wind speed forecasting based on Sparse Bayesian learning
Yun Wang, Haibo Wang, Dipti Srinivasan, et al.
Renewable Energy (2018) Vol. 132, pp. 43-60
Closed Access | Times Cited: 65
Automatic Image Cropping for Visual Aesthetic Enhancement Using Deep Neural Networks and Cascaded Regression
Guanjun Guo, Hanzi Wang, Chunhua Shen, et al.
IEEE Transactions on Multimedia (2018) Vol. 20, Iss. 8, pp. 2073-2085
Open Access | Times Cited: 65
Robust regression under the general framework of bounded loss functions
Saiji Fu, Yingjie Tian, Long Tang
European Journal of Operational Research (2023) Vol. 310, Iss. 3, pp. 1325-1339
Closed Access | Times Cited: 16
Two-dimensional LSTM soft sensor using noisy process data
Qiao Liu, Mingwei Jia, Xiaowei Guo, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 085001-085001
Open Access | Times Cited: 6
Sparse algorithm for robust LSSVM in primal space
Li Chen, Shuisheng Zhou
Neurocomputing (2017) Vol. 275, pp. 2880-2891
Open Access | Times Cited: 52
Support vector machine with truncated pinball loss and its application in pattern recognition
Liming Yang, Hongwei Dong
Chemometrics and Intelligent Laboratory Systems (2018) Vol. 177, pp. 89-99
Closed Access | Times Cited: 51
A class of new Support Vector Regression models
Pritam Anand, Reshma Rastogi, Suresh Chandra
Applied Soft Computing (2020) Vol. 94, pp. 106446-106446
Closed Access | Times Cited: 39
Correntropy long short term memory soft sensor for quality prediction in industrial polyethylene process
Qiao Liu, Mingwei Jia, Zengliang Gao, et al.
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 231, pp. 104678-104678
Closed Access | Times Cited: 24
A novel approach to deriving adaboost classifier weights using squared loss function for overlapping speech detection
Nassim Asbai, Hadjer Bounazou, Sihem Zitouni
Multimedia Tools and Applications (2025)
Closed Access
Robust statistics-based support vector machine and its variants: a survey
Manisha Singla, K.K. Shukla
Neural Computing and Applications (2019) Vol. 32, Iss. 15, pp. 11173-11194
Closed Access | Times Cited: 34
Robust support vector regression with generic quadratic nonconvex ε-insensitive loss
Yafen Ye, Junbin Gao, Yuan‐Hai Shao, et al.
Applied Mathematical Modelling (2020) Vol. 82, pp. 235-251
Open Access | Times Cited: 29
Robust extreme learning machine in the presence of outliers by iterative reweighted algorithm
Kuaini Wang, Jinde Cao, Huimin Pei
Applied Mathematics and Computation (2020) Vol. 377, pp. 125186-125186
Closed Access | Times Cited: 27
Robust GMM least square twin K-class support vector machine for urban water pipe leak recognition
Mingyang Liu, Yang Jin, Shuaiyong Li, et al.
Expert Systems with Applications (2022) Vol. 195, pp. 116525-116525
Closed Access | Times Cited: 18
Asymmetric and robust loss function driven least squares support vector machine
Xiaoxi Zhao, Saiji Fu, Yingjie Tian, et al.
Knowledge-Based Systems (2022) Vol. 258, pp. 109990-109990
Closed Access | Times Cited: 17
Robust semi-supervised extreme learning machine
Huimin Pei, Kuaini Wang, Qiang Lin, et al.
Knowledge-Based Systems (2018) Vol. 159, pp. 203-220
Closed Access | Times Cited: 30
A regularization on Lagrangian twin support vector regression
M. Tanveer, Kumar Shubham
International Journal of Machine Learning and Cybernetics (2015) Vol. 8, Iss. 3, pp. 807-821
Closed Access | Times Cited: 29
Least absolute deviation-based robust support vector regression
Chuanfa Chen, Yanyan Li, Changqing Yan, et al.
Knowledge-Based Systems (2017) Vol. 131, pp. 183-194
Closed Access | Times Cited: 26
The aLS-SVM based multi-task learning classifiers
Liyun Lu, Qiang Lin, Huimin Pei, et al.
Applied Intelligence (2017) Vol. 48, Iss. 8, pp. 2393-2407
Closed Access | Times Cited: 26
Mixture correntropy-based robust distance metric learning for classification
Chao Yuan, Changsheng Zhou, Jigen Peng, et al.
Knowledge-Based Systems (2024) Vol. 295, pp. 111791-111791
Closed Access | Times Cited: 2
Self-adaptive robust nonlinear regression for unknown noise via mixture of Gaussians
Haibo Wang, Yun Wang, Qinghua Hu
Neurocomputing (2017) Vol. 235, pp. 274-286
Closed Access | Times Cited: 24
A Robust Regression Framework with Laplace Kernel-Induced Loss
Liming Yang, Zhuo Ren, Yidan Wang, et al.
Neural Computation (2017) Vol. 29, Iss. 11, pp. 3014-3039
Closed Access | Times Cited: 24
Robust and optimal epsilon-insensitive Kernel-based regression for general noise models
Ömer Karal
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105841-105841
Closed Access | Times Cited: 6
Robust semi-supervised support vector machines with Laplace kernel-induced correntropy loss functions
Hongwei Dong, Liming Yang, Xue Wang
Applied Intelligence (2020) Vol. 51, Iss. 2, pp. 819-833
Closed Access | Times Cited: 17
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