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  2. Backpropagation - Wikipedia

    en.wikipedia.org/wiki/Backpropagation

    This is the reason why backpropagation requires that the activation function be differentiable. (Nevertheless, the ReLU activation function, which is non-differentiable at 0, has become quite popular, e.g. in AlexNet) The first factor is straightforward to evaluate if the neuron is in the output layer, because then = and

  3. Backpropagation through time - Wikipedia

    en.wikipedia.org/wiki/Backpropagation_through_time

    Back_Propagation_Through_Time(a, y) // a[t] is the input at time t. y[t] is the output Unfold the network to contain k instances of f do until stopping criterion is met: x := the zero-magnitude vector // x is the current context for t from 0 to n − k do // t is time. n is the length of the training sequence Set the network inputs to x, a[t ...

  4. Curiously recurring template pattern - Wikipedia

    en.wikipedia.org/wiki/Curiously_recurring...

    It is important to note that counter<X> and counter<Y> are two separate classes and this is why they will keep separate counts of Xs and Ys. In this example of CRTP, this distinction of classes is the only use of the template parameter (T in counter<T>) and the reason why we cannot use a simple un-templated base class.

  5. Universal approximation theorem - Wikipedia

    en.wikipedia.org/wiki/Universal_approximation...

    Universal approximation theorems are existence theorems: They simply state that there exists such a sequence ,,, and do not provide any way to actually find such a sequence. They also do not guarantee any method, such as backpropagation, might actually find such a sequence. Any method for searching the space of neural networks, including ...

  6. Delta rule - Wikipedia

    en.wikipedia.org/wiki/Delta_rule

    Next we rewrite in the last term as the sum over all weights of each weight times its corresponding input : = ′ [] Because we are only concerned with the i {\\displaystyle i} th weight, the only term of the summation that is relevant is x i w j i {\\displaystyle x_{i}w_{ji}} .

  7. C (programming language) - Wikipedia

    en.wikipedia.org/wiki/C_(programming_language)

    This is an accepted version of this page This is the latest accepted revision, reviewed on 17 January 2025. General-purpose programming language "C programming language" redirects here. For the book, see The C Programming Language. Not to be confused with C++ or C#. C Logotype used on the cover of the first edition of The C Programming Language Paradigm Multi-paradigm: imperative (procedural ...

  8. "Hello, World!" program - Wikipedia

    en.wikipedia.org/wiki/"Hello,_World!"_program

    program is usually a simple computer program that emits (or displays) to the screen (often the console) a message similar to "Hello, World!". A small piece of code in most general-purpose programming languages , this program is used to illustrate a language's basic syntax .

  9. Almeida–Pineda recurrent backpropagation - Wikipedia

    en.wikipedia.org/wiki/Almeida–Pineda_recurrent...

    Almeida–Pineda recurrent backpropagation is an extension to the backpropagation algorithm that is applicable to recurrent neural networks. It is a type of supervised learning . It was described somewhat cryptically in Richard Feynman 's senior thesis, and rediscovered independently in the context of artificial neural networks by both Fernando ...