A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …

Rapid developments in hardware, software, and communication technologies have
facilitated the emergence of Internet-connected sensory devices that provide observations …

The classification problem is closely related to the clustering problem discussed in Chaps. 6
and 7. While the clustering problem is that of determining similar groups of data points, the …

To solve the problems of low accuracy, low real-time performance, poor robustness and
others caused by the complex environment, this paper proposes a face mask recognition …

This is the first comprehensive introduction to Support Vector Machines (SVMs), a new
generation learning system based on recent advances in statistical learning theory. SVMs …

The output of a classifier should be a calibrated posterior probability to enable post-
processing. Ëtandard ËVMs do not provide such probabilities. One method to create …

My first exposure to Support Vector Machines came this spring when heard Sue Dumais
present impressive results on text categorization using this analysis technique. This issue's …

Training a support vector machine SVM leads to a quadratic optimization problem with
bound constraints and one linear equality constraint. Despite the fact that this type of …

The number of microbiome-related studies has notably increased the availability of data on
human microbiome composition and function. These studies provide the essential material …