TensorLy: Tensor Learning in Python

Jean Kossaifi, Yannis Panagakis, Maja Pantic

    Research output: Contribution to conferencePaperpeer-review

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    Abstract

    Tensor methods are gaining increasing traction in machine learning. However, there are scant to no resources available to perform tensor learning and decomposition in Python. To answer this need we developed TensorLy. TensorLy is a state of the art general purpose library for tensor learning. Written in Python, it aims at following the same standard adopted by the main projects of the Python scientific community and fully integrating with these. It allows for fast and straightforward tensor decomposition and learning and comes with exhaustive tests, thorough documentation and minimal dependencies. It can be easily extended and its BSD licence makes it suitable for both academic and commercial applications. TensorLy is available at https://github.com/tensorly/tensorly.
    Original languageUndefined
    Number of pages6
    Publication statusPublished - 29 Oct 2016
    EventProceedings of Tensor-Learn Workshop 2016 - Barcelona, Spain
    Duration: 10 Dec 201610 Dec 2016

    Workshop

    WorkshopProceedings of Tensor-Learn Workshop 2016
    Period10/12/1610/12/16
    Other10 Dec 2016

    Keywords

    • EWI-27554
    • HMI-HF: Human Factors
    • IR-103942

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