He’s credited with coming up with the first support vector machine (SVM) algorithm. SVMs are widely used today for machine learning purposes.

In this paper, a novel hybrid approach integrating genetic algorithm (GA) and support vector machines (SVM) is proposed to conduct the key factor exploration tasks in the core competitiveness ...

The Annals of Statistics, Vol. 36, No. 2 (Apr., 2008), pp. 489-531 (43 pages) The support vector machine (SVM) algorithm is well known to the computer learning community for its very good practical ...

Figure 2. SVM Classification After the support vectors and best separating line have been determined, it's easy to classify a new input vector/point. There are several algorithms that can be used to ...

Here, researchers from Beijing Institute of Nanoenergy and Nanosystems (Chinese Academy of Sciences) and Yonsei University present the latest progress in neuromorphic computing by integrating various ...

Medical datasets often present a major challenge for machine learning models: skewness in continuous variables such as age, tumor size, and survival months. This skewness can undermine the assumptions ...

"A building is only as strong as its foundation" is a common adage to signify the importance of having a stable and solid base to build upon. The type and design of foundation are important for ...