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In nonparametric statistics, a kernel is a weighting function used in non-parametric estimation techniques. Kernels are used in kernel density estimation to estimate random variables ' density functions, or in kernel regression to estimate the conditional expectation of a random variable. Kernels are also used in time-series, in the use of the ...
kernelcare .com. KernelCare is a live kernel patching service that provides security patches and bugfixes for a range of popular Linux kernels [2] that can be installed without rebooting the system. [3] KernelCare software is a commercial product. The first beta was introduced in March 2014 and it was commercially launched in May 2014.
ntoskrnl.exe (short for Windows NT operating system kernel executable ), also known as the kernel image, contains the kernel and executive layers of the Microsoft Windows NT kernel, and is responsible for hardware abstraction, process handling, and memory management. In addition to the kernel and executive layers, it contains the cache manager ...
Kernel (image processing) In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more. This is accomplished by doing a convolution between the kernel and an image. Or more simply, when each pixel in the output image is a function of the nearby pixels (including ...
For instance, Microsoft Windows on x86-64 uses the GS segment to point to the Thread Environment Block, a small data structure for each thread, which contains information about exception handling, thread-local variables, and other per-thread state. Similarly, the Linux kernel uses the GS segment to store per-CPU data.
In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These methods involve using linear classifiers to solve nonlinear problems. [1] The general task of pattern analysis is to find and study general types of relations (for example clusters, rankings ...
After a system has experienced an oops, some internal resources may no longer be operational. Thus, even if the system appears to work correctly, undesirable side effects may have resulted from the active task being killed. A kernel oops often leads to a kernel panic when the system attempts to use resources that have been lost. Some kernels ...
Kernel smoother. A kernel smoother is a statistical technique to estimate a real valued function as the weighted average of neighboring observed data. The weight is defined by the kernel, such that closer points are given higher weights. The estimated function is smooth, and the level of smoothness is set by a single parameter.