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ensmallen (C++ library)

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Stable release
1.11 / November 28, 2018; 2 years ago (2018-11-28)[1]
Written inC++
    Operating systemCross-platform
    Available inEnglish
    TypeSoftware library
    LicenseBSD 3-clause (open source)

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    ensmallen is a library of mathematical optimization algorithms for the C++ programming language. It provides a simple set of abstractions for writing an objective function to optimize. It also provides a large set of optimizers that can be used for virtually any mathematical optimization task. These include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization[2].

    It is open-source software distributed under the permissive 3-clause BSD license, making it applicable for the development of both open source and proprietary software.

    ensmallen is used by the mlpack library as an aid in the implementation of many of machine learning algorithms.

    Available Optimizers[edit]

    • many forms of stochastic gradient descent (including AdaGrad, RMSProp, Adam)
    • many forms of Quasi-Newton methods (including L-BFGS and Augmented Lagrangian method)
    • CMA-ES
    • Conditional gradient descent
    • Frank–Wolfe algorithm
    • Simulated annealing
    • Grid search

    See also[edit]

    Other articles of the topic Free and open-source software : Potato Open Sauce Project, SoX, Gede (software), Ring (programming language), MIXR, Ruqqus, Marscoin
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    • List of optimization software
    • List of numerical analysis software
    • List of numerical libraries
    • Numerical linear algebra
    • Scientific computing


    1. "ensmallen documentation / changelog". Retrieved 12 December 2018.
    2. Shikhar Bhardwaj, Ryan R. Curtin, Yannis Mentekidis, Marcus Edel, Conrad Sanderson (2018). ensmallen: a flexible C++ library for efficient function optimization. Workshop on Systems for ML and Open Source Software at NIPS / NeurIPS. doi:10.5281/zenodo.2008650.CS1 maint: Multiple names: authors list (link)

    External links[edit]

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