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 ...

Kernel methods have emerged as a powerful tool in adaptive filtering and system identification, enabling the processing and modelling of complex, nonlinear relationships in dynamic systems. By mapping ...

This is a preview. Log in through your library . Abstract When conducting line transect sampling to estimate the abundance of a clustered wildlife population, detection of a school depends not only on ...

A kernel method for the estimation of quantal dose-response curves is considered. In contrast to parametric modeling, this local smoothing method does not require any assumptions beyond smoothness of ...

Quantum information scientists have introduced a new method for machine learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new ...

SHENZHEN, China, May 20, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, announced the development of a new quantum ...

Researchers have successfully demonstrated quantum speedup in kernel-based machine learning. Scientists say they have made a breakthrough after developing a quantum computing technique to run machine ...