Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly
emerging efficient machine learning techniques which offer promising solutions for …

In this paper the idea of Self-Optimizing Machining Systems (SOMS) is introduced and
discussed. Against the background of Industry 4.0, here the focus is the technological level …

Motor imagery brain-computer interface (BCI) systems require accurate and fast recognition
of brain activity patterns for reliable communication and interaction. Achieving this accuracy …

Parameters optimization is a research hotspot of SVM and has gained increasing interest
from various research fields. Compared with other optimization algorithms, genetic-based …

Convolutional neural networks (CNNs) have attracted researchers' increasing attention for
almost three decades now, achieving superior results in such domains as computer vision …

The Sentiment Analysis is used for the text analysing, and classification of the text attitude.
We are using the computing advancement in the form of Machine Learning (ML) and …

Abstract Least Squares Twin Support Vector Machine (LST-SVM) has been shown to be an
efficient and fast algorithm for binary classification. In many real-world applications, samples …

In the early days of social networking, a community was typically viewed as a collection of
user pro-files sharing common interests and likes. This community continued to grow by …

One of the major coal industry problems is the auto-oxidation of coal, which leads to fires
and human-induced disasters. This paper aims to use machine learning techniques and the …

In the field of machine learning, collected data always have additional features which are
always referred as privileged information. Privileged information learning is mainly used to …