One-class support vector classifiers: A survey

S Alam, SK Sonbhadra, S Agarwal… - Knowledge-Based …, 2020 - Elsevier
Over the past two decades, one-class classification (OCC) becomes very popular due to its
diversified applicability in data mining and pattern recognition problems. Concerning to …

DC programming and DCA: thirty years of developments

HA Le Thi, T Pham Dinh - Mathematical Programming, 2018 - Springer
The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …

Fast SVM classifier for large-scale classification problems

H Wang, G Li, Z Wang - Information Sciences, 2023 - Elsevier
Support vector machines (SVM), as one of effective and popular classification tools, have
been widely applied in various fields. However, they may incur prohibitive computational …

Robust statistics-based support vector machine and its variants: a survey

M Singla, KK Shukla - Neural Computing and Applications, 2020 - Springer
Support vector machines (SVMs) are versatile learning models which are used for both
classification and regression. Several authors have reported successful applications of SVM …

[HTML][HTML] A mathematical programming approach to SVM-based classification with label noise

V Blanco, A Japón, J Puerto - Computers & Industrial Engineering, 2022 - Elsevier
In this paper we propose novel methodologies to optimally construct Support Vector
Machine-based classifiers that take into account that label noise occur in the training …

Support Vector Machine Classifier via Soft-Margin Loss

H Wang, Y Shao, S Zhou, C Zhang… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Support vector machines (SVM) have drawn wide attention for the last two decades due to
its extensive applications, so a vast body of work has developed optimization algorithms to …

Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem

SMH Bamakan, H Wang, Y Shi - Knowledge-Based Systems, 2017 - Elsevier
Network intrusion detection problem is an ongoing challenging research area because of a
huge number of traffic volumes, extremely imbalanced data sets, multi-class of attacks …

Ramp loss one-class support vector machine; a robust and effective approach to anomaly detection problems

Y Tian, M Mirzabagheri, SMH Bamakan, H Wang, Q Qu - Neurocomputing, 2018 - Elsevier
Anomaly detection defines as a problem of finding those data samples, which do not follow
the patterns of the majority of data points. Among the variety of methods and algorithms …

Distributionally favorable optimization: A framework for data-driven decision-making with endogenous outliers

N Jiang, W **e - SIAM Journal on Optimization, 2024 - SIAM
A typical data-driven stochastic program seeks the best decision that minimizes the sum of a
deterministic cost function and an expected recourse function under a given distribution …

Fast truncated Huber loss SVM for large scale classification

H Wang, Y Shao - Knowledge-Based Systems, 2023 - Elsevier
Support vector machine (SVM), as a useful tool of classification, has been widely applied in
many fields. However, it may incur computationally infeasibility on very large sample …