Elastic net support vector machine (ENSVM) is an effective and popular classification
technique. It has been widely used in many practical applications. However, solving large …

Multi-label rank support vector machine (RankSVM) is an effective technique to deal with
multi-label classification problems, which has been widely used in various fields. However, it …

For multi-class classification, many existing methods, such as multiple weighted linear loss
twin support vector machine (MWLTSVM), construct multiple decision hyperplanes by …

Rank support vector machine (RSVM) is widely used in multilabel classification problems.
However, as the number of labels and instances soars, the training efficiency of the model …

Support vector machine (SVM) is one of the extremely effective classification tools, which
has been widely employed in real-world applications. However, it is time-consuming and …

Injecting soil conditioner into the soil during EPB shield construction is crucial for soil
enhancement. Foam agent consumption is common but developing their composition and …

Support vector machines (SVMs) are successful supervised learning models that analyze
data for classification and regression. Previous work has demonstrated the superiority of the …

To deal with outliers or heavy-tailed random errors in common high-dimensional data sets,
robust regressions are preferable selections and Rank Lasso is a notable model among …

As an important model in multi-label learning, ProSVM considers two problems
simultaneously: one is to distinguish the relevant labels from the irrelevant labels of …

Lasso is a popular method for high-dimensional applications in machine learning. In this
paper, we propose a novel variant of Lasso, named self-weighted Lasso (SWL). Self …