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 …

Support vector machine (SVM) is one of the most studied paradigms in the realm of machine
learning for classification and regression problems. It relies on vectorized input data …

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 …

Support vector machine (SVM) is widely recognized as an effective classification tool and
has demonstrated superior performance in diverse applications. However, for large-scale …

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 …

Support vector machine (SVM) is one of well-known supervised machine learning classifier
and is used widely in image classification, pattern recognition, disease diagnosis, etc …

In the domain of machine learning, the significance of the loss function is paramount,
especially in supervised learning tasks. It serves as a fundamental pillar that profoundly …

Softmax regression, a generalization of Logistic regression (LR) in the setting of multi-class
classification, has been widely used in many machine learning applications. However, the …

Support vector machine (SVM) has drawn wide attention in various fields, such as image
classification, pattern recognition and disease diagnosis and so on. Nevertheless, it requires …

In this article, an improved nonparallel support vector machine (INPSVM) is proposed for
pattern classification. INPSVM inherits almost all advantages of nonparallel support vector …