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  2. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    Examples include: [17] [18] Lang and Witbrock (1988) [19] trained a fully connected feedforward network where each layer skip-connects to all subsequent layers, like the later DenseNet (2016). In this work, the residual connection was the form x ↦ F ( x ) + P ( x ) {\displaystyle x\mapsto F(x)+P(x)} , where P {\displaystyle P} is a randomly ...

  3. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    Finding the global minimum solution of a Hartree-Fock problem [37] Upward planarity testing [8] Hospitals-and-residents problem with couples; Knot genus [38] Latin square completion (the problem of determining if a partially filled square can be completed) Maximum 2-satisfiability [3]: LO5

  4. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    Nontrivial problems can be solved using only a few nodes if the activation function is nonlinear. [ 1 ] Modern activation functions include the logistic ( sigmoid ) function used in the 2012 speech recognition model developed by Hinton et al; [ 2 ] the ReLU used in the 2012 AlexNet computer vision model [ 3 ] [ 4 ] and in the 2015 ResNet model ...

  5. Parsons problem - Wikipedia

    en.wikipedia.org/wiki/Parsons_problem

    Parsons problems are a form of an objective assessment in which respondents are asked to choose from a selection of code fragments, some subset of which comprise the problem solution. The Parsons problem format is used in the learning and teaching of computer programming .

  6. List of unsolved problems in computer science - Wikipedia

    en.wikipedia.org/wiki/List_of_unsolved_problems...

    The problem to determine all positive integers such that the concatenation of and in base uses at most distinct characters for and fixed [citation needed] and many other problems in the coding theory are also the unsolved problems in mathematics.

  7. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    In machine learning, the vanishing gradient problem is encountered when training neural networks with gradient-based learning methods and backpropagation. In such methods, during each training iteration, each neural network weight receives an update proportional to the partial derivative of the loss function with respect to the current weight ...

  8. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/.../Constraint_satisfaction_problem

    In the general case, constraint problems can be much harder, and may not be expressible in some of these simpler systems. "Real life" examples include automated planning, [6] [7] lexical disambiguation, [8] [9] musicology, [10] product configuration [11] and resource allocation. [12] The existence of a solution to a CSP can be viewed as a ...

  9. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    The subset sum problem (SSP) is a decision problem in computer science. In its most general formulation, there is a multiset S {\displaystyle S} of integers and a target-sum T {\displaystyle T} , and the question is to decide whether any subset of the integers sum to precisely T {\displaystyle T} . [ 1 ]