Machine learning is becoming the cornerstones of smart and autonomous systems. Machine
learning algorithms can be categorized into supervised learning (classification) and …

Support vector machine (SVM) is a robust machine learning model with high classification
accuracy. SVM is widely utilized for online classification in various real-time embedded …

Support vector machines (SVMs) are a powerful machine learning tool, providing state-of-
the-art accuracy to many classification problems. However, SVM classification is a …

Abstract The Support Vector Machine (SVM) is a common machine learning tool that is
widely used because of its high classification accuracy. Implementing SVM for embedded …

Support vector machines (SVMs) have proven to yield high accuracy and have been used
widespread in recent years. However, the standard versions of the SVM algorithm are very …

Support Vector Machines (SVMs) are a powerful supervised learning tool, providing state-of-
the-art accuracy at a cost of high computational complexity. The SVM classification suffers …

The relentless increase in data volume and complexity necessitates advancements in
machine learning methodologies that are more adaptable. In response to this challenge, we …

On-chip training of support vector machine (SVM) is limited by its low speed and large
resource cost. In this paper, a novel integrated circuit implementation of the modified …

This work demonstrates a hardware-efficient support vector machine (SVM) training
algorithm via the alternative direction method of multipliers (ADMM) optimizer. Low-rank …

Abstract Support Vector Machine (SVM) is a robust machine learning model that shows high
accuracy with different classification problems, and is widely used for various embedded …