Kernel methods and support vector machines (SVMs) serve as cornerstones in modern machine learning, offering robust techniques for both classification and regression tasks. At their core, kernel ...

Quantum algorithms based on quantum kernel methods have been investigated previously [1]. A quantum advantage is derived from the fact that it is possible to construct a family of datasets for which, ...

Here you will find the guidelines used by Methods Hub for tutorials. If you are preparing a method, check the guidelines used by Methods Hub for methods. A tutorial is an instructional resource that ...

The Linux Foundation's Greg Kroah-Hartman delivered a comprehensive talk this week on the current state and future challenges of Linux kernel security. Speaking at the Open Source Summit (OSS) Japan ...

Abstract: The authors combine feature-based kernel with extension path graph kernel into a multiple kernels learning method. Feature-based kernel method, extension path graph kernel method and ...

ABSTRACT: The speckle noise is considered one of the main causes of degradation in ultrasound image quality. Many despeckling filters have been proposed, which are always making a trade-off between ...

A number in bold font is the smallest value under each circumstance. In order to investigate whether criterion equating plays a different role in equating evaluation or not, four equating methods (EE, ...

Abstract: Conventional PET reconstruction produces noisy images. Recently proposed techniques such as the MR-guided kernel method have been employed to reduce the impact of noise, whilst retaining ...

"# Quantum Kernel Methods for IRIS dataset classification with [TorchQuantum](https://github.com/mit-han-lab/torchquantum).\n", "Quantum circuit can transfer the data ...