Kernel PCA (KPCA) is a powerful machine learning technique which has been used for visualization, dimension reduction, and novelty detection. The folllowing [1] SAS technical report contains various ...

In this example, we investigate the performance of fast KPCA, which is based on a low-rank approximation method. The letter recognition data set that is used in this example is from UCI ...

Semantic Kernel distinguishes between semantic functions, templated prompts, and native functions, i.e. the native computer code that processes data for use in the LLM’s semantic functions.

Concatenated codes proposed by Forney are used extensively in digital communication. In this paper, concatenated kernel codes, a class of group codes is constructed with inner code and outer code.

The Linux kernel has a monolithic architecture, which means that the whole kernel code runs in kernel space and shares the same address space. ... This behavior is very common in the kernel—for ...