Tensor train decomposition on tensorflow (T3F)

Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan Oseledets

    Research output: Contribution to journalArticlepeer-review

    16 Citations (Scopus)

    Abstract

    Tensor Train decomposition is used across many branches of machine learning. We present T3F-a library for Tensor Train decomposition based on TensorFlow. T3F supports GPU execution, batch processing, automatic differentiation, and versatile functionality for the Riemannian optimization framework, which takes into account the underlying manifold structure to construct efficient optimization methods. The library makes it easier to implement machine learning papers that rely on the Tensor Train decomposition. T3F includes documentation, examples and 94% test coverage.

    Original languageEnglish
    JournalJournal of Machine Learning Research
    Volume21
    Publication statusPublished - 1 Mar 2020

    Keywords

    • Gpu
    • Software
    • Tensor decomposition
    • Tensor train
    • Tensorflow

    Fingerprint

    Dive into the research topics of 'Tensor train decomposition on tensorflow (T3F)'. Together they form a unique fingerprint.

    Cite this