Kernel Methods For Machine Learning
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Kernel Methods For Machine Learning
Kernel may refer to: Computing * Kernel (operating system), the central component of most operating systems * Kernel (image processing), a matrix used for image convolution * Compute kernel, in GPGPU programming * Kernel method, in machine learning * Kernelization, a technique for designing efficient algorithms ** Kernel, a routine that is executed in a vectorized loop, for example in general-purpose computing on graphics processing units *KERNAL, the Commodore operating system Mathematics Objects * Kernel (algebra), a general concept that includes: ** Kernel (linear algebra) or null space, a set of vectors mapped to the zero vector ** Kernel (category theory), a generalization of the kernel of a homomorphism ** Kernel (set theory), an equivalence relation: partition by image under a function ** Difference kernel, a binary equalizer: the kernel of the difference of two functions Functions * Kernel (geometry), the set of points within a polygon from which the whole polygon boun ...
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Kernel (operating System)
A kernel is a computer program at the core of a computer's operating system that always has complete control over everything in the system. The kernel is also responsible for preventing and mitigating conflicts between different processes. It is the portion of the operating system code that is always resident in memory and facilitates interactions between hardware and software components. A full kernel controls all hardware resources (e.g. I/O, memory, cryptography) via device drivers, arbitrates conflicts between processes concerning such resources, and optimizes the use of common resources, such as CPU, cache, file systems, and network sockets. On most systems, the kernel is one of the first programs loaded on startup (after the bootloader). It handles the rest of startup as well as memory, peripherals, and input/output (I/O) requests from software, translating them into data-processing instructions for the central processing unit. The critical code of the kernel is usua ...
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Stochastic Kernel
In probability theory, a Markov kernel (also known as a stochastic kernel or probability kernel) is a map that in the general theory of Markov processes plays the role that the transition matrix does in the theory of Markov processes with a finite state space. Formal definition Let (X,\mathcal A) and (Y,\mathcal B) be measurable spaces. A ''Markov kernel'' with source (X,\mathcal A) and target (Y,\mathcal B), sometimes written as \kappa:(X,\mathcal)\to(Y,\mathcal), is a function \kappa : \mathcal B \times X \to ,1/math> with the following properties: # For every (fixed) B_0 \in \mathcal B, the map x \mapsto \kappa(B_0, x) is \mathcal A- measurable # For every (fixed) x_0 \in X, the map B \mapsto \kappa(B, x_0) is a probability measure on (Y, \mathcal B) In other words it associates to each point x \in X a probability measure \kappa(dy, x): B \mapsto \kappa(B, x) on (Y,\mathcal B) such that, for every measurable set B\in\mathcal B, the map x\mapsto \kappa(B, x) is measur ...
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Kernel (neurotechnology Company)
HI, LLC, doing business as Kernel, is an American company that has developed a non-invasive neuroimaging technology. It is a privately held company headquartered in Los Angeles, California. The company was founded in 2016 by Bryan Johnson. History Johnson founded Kernel in 2016 with a $54 million investment and began researching neuroprosthetics, devices implanted into the brain that mimic, substitute, or assist brain functions. In May 2020, Kernel introduced two brain-activity monitoring devices, Flux and Flow. The Flow device can both see and record brain activity. Kernel also introduced "Sound ID," a software that can tell what speech or song a person is listening to just from brain data. The company was featured in the 2020 documentary, ''I Am Human,'' about brain–machine interfaces. Kernel raised $53 million in 2020. Kernel Flow Kernel Flow is a wearable time-domain functional near-infrared spectroscopy (TD-fNIRS) system. fNIRs uses infrared light to measure chang ...
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Kernel (agriculture Company)
Kernel Holding S.A. () is the largest producer of sunflower oil in Ukraine. It operates under the brands ''Shchedry Dar'', ''Stozhar'' and ''Chumak Zolota'', exports oils and grain worldwide, and provides storage for grains and seeds. It produces 8% of sunflower oil in the world and its products are supplied to sixty countries. It operates 28 grain elevators in Ukraine with a total storage capacity of 2.34 million tons of grain, the highest among private-sector companies in the country. History It was established in 1994 by Andriy Verevskyi. Kernel launched an initial public offering on the Warsaw Stock Exchange in 2007, becoming the second Ukrainian company to hold an IPO in Warsaw. In 2020, '' Forbes Ukraine'' ranked Kernel as the third-largest private-sector company in Ukraine by revenue. ''Forbes Ukraine'' ranked Kernel the fourth-best employer in its 2021 list of the fifty best employers in the country. The company is actively investing in the development of small and ...
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Atomic Nucleus
The atomic nucleus is the small, dense region consisting of protons and neutrons at the center of an atom, discovered in 1911 by Ernest Rutherford at the Department_of_Physics_and_Astronomy,_University_of_Manchester , University of Manchester based on the 1909 Geiger–Marsden experiments, Geiger–Marsden gold foil experiment. After the discovery of the neutron in 1932, models for a nucleus composed of protons and neutrons were quickly developed by Dmitri Ivanenko and Werner Heisenberg. An atom is composed of a positively charged nucleus, with a cloud of negatively charged electrons surrounding it, bound together by electrostatic force. Almost all of the mass of an atom is located in the nucleus, with a very small contribution from the electron cloud. Protons and neutrons are bound together to form a nucleus by the nuclear force. The diameter of the nucleus is in the range of () for hydrogen (the diameter of a single proton) to about for uranium. These dimensions are much ...
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Wheat Berry
A wheat berry, or wheatberry, is a whole wheat kernel, composed of the bran, germ, and endosperm, without the husk. Botanically, it is a type of fruit called a caryopsis. Wheat berries are eaten as a grain, have a tan to reddish-brown color, and can vary in gluten and protein content from 6–9% ("soft") to 10–14% ("hard"). They are often added to salads or baked into bread to add a chewy texture. If wheat berries are milled, whole-wheat flour is produced. Wheat berries are similar to barley, rye, and kamut. Wheat berries are the primary ingredient in an Eastern European Christmas porridge called ''kutia''. In France, cooked durum wheat berries are commonly eaten as a side dish instead of rice or corn. This side dish is often called ''ebly'', from the name of the first brand of prepared wheat berries. In Romania and other Eastern European countries, the wheat berries (arpacas) are used in a special sweet dish called koliva for Christian Orthodox ritual. Puffed wheat ...
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Palm Kernel
The palm kernel is the edible seed of the oil palm fruit. The fruit yields two distinct oils: palm oil derived from the outer parts of the fruit, and palm kernel oil derived from the kernel. The pulp left after oil is rendered from the kernel is formed into "palm kernel cake", used either as high-protein feed for dairy cattle or burned in boilers to generate electricity for palm oil mills and surrounding villages. Uses Palm kernel cake is most commonly produced by economical screw press, less frequently via more expensive solvent extraction. Palm kernel cake is a high-fibre, medium-grade protein feed best suited to ruminants. Among other similar fodders, palm kernel cake is ranked a little higher than copra cake and cocoa pod husk, but lower than fish meal and groundnut cake, especially in its protein value. Composed of 16% fiber, palm kernel cake also has a high phosphorus-to-calcium ratio and contains such essential elements as magnesium, iron, and zinc. The typica ...
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Corn Kernel
Corn kernels are the fruits of Maize, corn (called maize in many countries). Maize is a grain, and the kernels are used in cooking as a vegetable or a source of starch. The kernel comprise endosperm, Germ (grain), germ, pericarp, and tip cap. Description Corn kernels are the fruits of maize. Maize is a grain, and the kernels are used in cooking as a vegetable or a source of starch. The kernels can be of various colors: blackish, blue corn, bluish-gray, purple, green, red, white and yellow. The kernel of maize consists of a pericarp (fruit wall) fused to the seed coat. This type of fruit is typical of the Poaceae, grasses and is called a caryopsis. Maize kernels are frequently and incorrectly referred to as seeds. The kernels are about the size of peas, and adhere in regular rows round a white, pithy substance, which forms the ear. Typical shapes of corn kernels include horse-tooth shape, sphereical cone shape, and spherical shape. Endosperm About 82 percent of the corn ...
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Apricot Kernel
An apricot kernel is the apricot seed located within the fruit endocarp, which forms a hard shell around the seed called the pyrena (stone or pit). The kernel contains amygdalin, a poisonous compound, in concentrations that vary between cultivars. Together with the related synthetic compound laetrile, amygdalin has been marketed as an alternative cancer treatment. However, studies have found the compounds to be ineffective for treating cancer. __TOC__ Use The kernel is an economically significant byproduct of fruit processing and the extracted oil and resulting press cake have value. Apricot kernel oil gives Disaronno and some other types of amaretto their almond-like flavor. They are also used in Amaretti di Saronno. In Mandarin Chinese, the term () can refer to either apricot kernels or almonds. Two varieties of apricot kernels are used in Chinese cuisines; a more bitter northern variety and a sweeter southern one. In Cantonese cuisine the two are often mixed, whil ...
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Seed
In botany, a seed is a plant structure containing an embryo and stored nutrients in a protective coat called a ''testa''. More generally, the term "seed" means anything that can be Sowing, sown, which may include seed and husk or tuber. Seeds are the product of the ripened ovule, after the embryo sac is fertilization, fertilized by Pollen, sperm from pollen, forming a zygote. The embryo within a seed develops from the zygote and grows within the mother plant to a certain size before growth is halted. The formation of the seed is the defining part of the process of reproduction in seed plants (spermatophytes). Other plants such as ferns, mosses and marchantiophyta, liverworts, do not have seeds and use water-dependent means to propagate themselves. Seed plants now dominate biological Ecological niche, niches on land, from forests to grasslands both in hot and cold climates. In the flowering plants, the ovary ripens into a fruit which contains the seed and serves to disseminate ...
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Reproducing Kernel Hilbert Space
In functional analysis, a reproducing kernel Hilbert space (RKHS) is a Hilbert space of functions in which point evaluation is a continuous linear functional. Specifically, a Hilbert space H of functions from a set X (to \mathbb or \mathbb) is an RKHS if the point-evaluation functional L_x:H\to\mathbb, L_x(f)=f(x), is continuous for every x\in X. Equivalently, H is an RKHS if there exists a function K_x \in H such that, for all f \in H,\langle f, K_x \rangle = f(x).The function K_x is then called the ''reproducing kernel'', and it reproduces the value of f at x via the inner product. An immediate consequence of this property is that convergence in norm implies uniform convergence on any subset of X on which \, K_x\, is bounded. However, the converse does not necessarily hold. Often the set X carries a topology, and \, K_x\, depends continuously on x\in X, in which case: convergence in norm implies uniform convergence on compact subsets of X. It is not entirely straightforwar ...
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Kernel Trick
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. The general task of pattern analysis is to find and study general types of relations (for example clusters, rankings, principal components, correlations, classifications) in datasets. For many algorithms that solve these tasks, the data in raw representation have to be explicitly transformed into feature vector representations via a user-specified ''feature map'': in contrast, kernel methods require only a user-specified ''kernel'', i.e., a similarity function over all pairs of data points computed using inner products. The feature map in kernel machines is infinite dimensional but only requires a finite dimensional matrix from user-input according to the representer theorem. Kernel machines are slow to compute for datasets larger than a couple of thousand ...
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