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  2. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    Layer normalization (LayerNorm) [13] is a popular alternative to BatchNorm. Unlike BatchNorm, which normalizes activations across the batch dimension for a given feature, LayerNorm normalizes across all the features within a single data sample. Compared to BatchNorm, LayerNorm's performance is not affected by batch size.

  3. NACK-Oriented Reliable Multicast - Wikipedia

    en.wikipedia.org/wiki/NACK-Oriented_Reliable...

    A NORM node refers to an individual node taking part in a NORM session. Each node has a unique identifier. When a node transmits a NORM message, this identifier is noted as the source_id. A NORM instance refers to an individual node in the context of a continuous segment of a NORM session. When a node joins a NORM session, it has a unique node ...

  4. Multilayer perceptron - Wikipedia

    en.wikipedia.org/wiki/Multilayer_perceptron

    In 2021, a very simple NN architecture combining two deep MLPs with skip connections and layer normalizations was designed and called MLP-Mixer; its realizations featuring 19 to 431 millions of parameters were shown to be comparable to vision transformers of similar size on ImageNet and similar image classification tasks.

  5. Batch normalization - Wikipedia

    en.wikipedia.org/wiki/Batch_normalization

    Batch normalization (also known as batch norm) is a method used to make training of artificial neural networks faster and more stable through normalization of the layers' inputs by re-centering and re-scaling. It was proposed by Sergey Ioffe and Christian Szegedy in 2015.

  6. Comparison of OS emulation or virtualization apps on Android

    en.wikipedia.org/wiki/Comparison_of_OS_Emulation...

    There are many apps in Android that can run or emulate other operating systems, via utilizing hardware support for platform virtualization technologies, or via terminal emulation. Some of these apps support having more than one emulation/virtual file system for different OS profiles, thus the ability to have or run multiple OS's.

  7. Layer (deep learning) - Wikipedia

    en.wikipedia.org/wiki/Layer_(Deep_Learning)

    In this layer, the network detects edges, textures, and patterns. The outputs from this layer are then fed into a fully-connected layer for further processing. See also: CNN model. The Pooling layer [5] is used to reduce the size of data input. The Recurrent layer is used for text processing with a memory function. Similar to the Convolutional ...

  8. Hardware abstraction - Wikipedia

    en.wikipedia.org/wiki/Hardware_abstraction

    A hardware abstraction layer (HAL) is an abstraction layer, implemented in software, between the physical hardware of a computer and the software that runs on that computer. . Its function is to hide differences in hardware from most of the operating system kernel, so that most of the kernel-mode code does not need to be changed to run on systems with different hardwa

  9. 5G network slicing - Wikipedia

    en.wikipedia.org/wiki/5G_network_slicing

    5G network slicing is a network architecture that enables the multiplexing of virtualized and independent logical networks on the same physical network infrastructure. [1] [2] Each network slice is an isolated end-to-end network tailored to fulfill diverse requirements requested by a particular application.