Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces.

More recently, the kernel method has been introduced in quantum machine learning with great success.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression using the C# language. NW kernel regression is simple to implement and is ...

The addition of heterogenous memory management to the Linux kernel will unlock new ways to speed up GPUs, and potentially other kinds of machine learning hardware ...

Yenming J. Chen, Yeong-Cheng Liou, Wen-Hsien Ho, Jinn-Tsong Tsai, Chia-Chuan Liu, Kao-Shing Hwang, Non-destructive acoustic screening of pineapple ripeness by unsupervised machine learning and Wavelet ...