Explore topic-wise fullforms in Computing

INFO: Full form for KMS is Key Management Specification in Computing category
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INFO: Full form for KMS is Key Management Schemes in Computing category
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In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). 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 pairs of data points in raw representation.

Kernel methods owe their name to the use of kernel functions, which enable them to operate in a high-dimensional, implicit feature space without ever computing the coordinates of the data in that space, but rather by simply computing the inner products between the images of all pairs of data in the feature space. This operation is often computationally cheaper than the explicit computation of the coordinates. This approach is called the "kernel trick". Kernel functions have been introduced for sequence data, graphs, text, images, as well as vectors.

Algorithms capable of operating with kernels include the kernel perceptron, support-vector machines (SVM), Gaussian processes, principal components analysis (PCA), canonical correlation analysis, ridge regression, spectral clustering, linear adaptive filters and many others.

Most kernel algorithms are based on convex optimization or eigenproblems and are statistically well-founded. Typically, their statistical properties are analyzed using statistical learning theory (for example, using Rademacher complexity).

INFO: Full form for KMs is Kernel Based Mode Setting in Computing category
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INFO: Full form for KMS is Kernel Memory Scanning in Computing category
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INFO: Full form for KMS is Knowledge Management Software in Computing category
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INFO: Full form for MEM is MEMory - to display memory allocation and available in Computing category
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INFO: Full form for MEM is Maximun Entropy Modeling in Computing category
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INFO: Full form for MEM is Macro Editor Macro in Computing category
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INFO: Full form for MEM is Mcafee Enterprise Management in Computing category
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INFO: Full form for MEM is Metro Ethernet Manager in Computing category
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INFO: Full form for MEM is Multi Entity Management in Computing category
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Windows Media is a discontinued multimedia framework for media creation and distribution for Microsoft Windows. It consists of a software development kit (SDK) with several application programming interfaces (API) and a number of prebuilt technologies, and is the replacement of NetShow technologies.

The Windows Media SDK was replaced by Media Foundation when Windows Vista was released.

INFO: Full form for WMF is Workload Monitoring Function in Computing category
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INFO: Full form for WMF is Wireless Multimedia Forum in Computing category
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In mathematics, a Markov decision process (MDP) is a discrete-time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying optimization problems solved via dynamic programming. MDPs were known at least as early as the 1950s; a core body of research on Markov decision processes resulted from Ronald Howard's 1960 book, Dynamic Programming and Markov Processes. They are used in many disciplines, including robotics, automatic control, economics and manufacturing. The name of MDPs comes from the Russian mathematician Andrey Markov as they are an extension of Markov chains.

At each time step, the process is in some state s {\displaystyle s} , and the decision maker may choose any action a {\displaystyle a} that is available in state s {\displaystyle s} . The process responds at the next time step by randomly moving into a new state s ′ {\displaystyle s'} , and giving the decision maker a corresponding reward R a ( s , s ′ ) {\displaystyle R_{a}(s,s')} .

The probability that the process moves into its new state s ′ {\displaystyle s'} is influenced by the chosen action. Specifically, it is given by the state transition function P a ( s , s ′ ) {\displaystyle P_{a}(s,s')} . Thus, the next state s ′ {\displaystyle s'} depends on the current state reference

INFO: Full form for MDP is Multi Disc Programme in Computing category
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INFO: Full form for MDP is Modem Distribution Panel in Computing category
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INFO: Full form for MDP is Market Data Processor in Computing category
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INFO: Full form for MDP is Multidimensional Data Provider in Computing category
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INFO: Full form for MDP is Media Disc Player in Computing category
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INFO: Full form for MDP is Multimedia Direct Playing in Computing category
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