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  2. 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 ...

  3. 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.

  4. 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.

  5. Object-oriented programming - Wikipedia

    en.wikipedia.org/wiki/Object-oriented_programming

    In object oriented programming, objects provide a layer which can be used to separate internal from external code and implement abstraction and encapsulation. External code can only use an object by calling a specific instance method with a certain set of input parameters, reading an instance variable, or writing to an instance variable.

  6. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    For instance, consider the hyperbolic tangent activation function. The gradients of this function are in range [-1,1]. The product of repeated multiplication with such gradients decreases exponentially. The inverse problem, when weight gradients at earlier layers get exponentially larger, is called the exploding gradient problem.

  7. OPC Unified Architecture - Wikipedia

    en.wikipedia.org/wiki/OPC_Unified_Architecture

    Code directly on the network layer (similar to the current .Net implementation) and de-serialize in Java. This saves one data copy execution, but still depends on the C stack. Write a native Java OPC UA stack. This was observed to be the most portable, but estimated to take the most engineering effort to implement.

  8. Instance (computer science) - Wikipedia

    en.wikipedia.org/wiki/Instance_(computer_science)

    In computer science, an instance is an occurrence of a software element that is based on a type definition. When created, an occurrence is said to have been instantiated , and both the creation process and the result of creation are called instantiation .

  9. 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 ...