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  2. Nonlinear programming - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_programming

    SciPy (de facto standard for scientific Python) has scipy.optimize solver, which includes several nonlinear programming algorithms (zero-order, first order and second order ones). IPOPT (C++ implementation, with numerous interfaces including C, Fortran, Java, AMPL, R, Python, etc.) is an interior point method solver (zero-order, and optionally ...

  3. Nonlinear gameplay - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_gameplay

    A nonlinear game will allow greater player freedom than a linear game. For example, a nonlinear game may permit multiple sequences to finish the game, a choice between paths to victory, different types of victory, or optional side-quests and subplots.

  4. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    In addition to performing linear classification, SVMs can efficiently perform non-linear classification using the kernel trick, representing the data only through a set of pairwise similarity comparisons between the original data points using a kernel function, which transforms them into coordinates in a higher-dimensional feature space.

  5. SNOPT - Wikipedia

    en.wikipedia.org/wiki/SNOPT

    SNOPT, for Sparse Nonlinear OPTimizer, is a software package for solving large-scale nonlinear optimization problems written by Philip Gill, Walter Murray and Michael Saunders. SNOPT is mainly written in Fortran , but interfaces to C , C++ , Python and MATLAB are available.

  6. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...

  7. Gradient descent - Wikipedia

    en.wikipedia.org/wiki/Gradient_descent

    Gradient descent can also be used to solve a system of nonlinear equations. Below is an example that shows how to use the gradient descent to solve for three unknown variables, x 1, x 2, and x 3. This example shows one iteration of the gradient descent. Consider the nonlinear system of equations

  8. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    Nonlinear When the activation function is non-linear, then a two-layer neural network can be proven to be a universal function approximator. [6] This is known as the Universal Approximation Theorem. The identity activation function does not satisfy this property.

  9. Nonlinear narrative - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_narrative

    Nonlinear narrative, disjointed narrative, or disrupted narrative is a narrative technique where events are portrayed, for example, out of chronological order or in other ways where the narrative does not follow the direct causality pattern of the events featured, such as parallel distinctive plot lines, dream immersions or narrating another story inside the main plot-line.