TensorFlow ManOpt: a library for optimization on Riemannian manifolds

• URL: http://arxiv.org/abs/2105.13921v1
• Date: Thu, 27 May 2021 10:42:09 GMT
• Title: TensorFlow ManOpt: a library for optimization on Riemannian manifolds
• Authors: Oleg Smirnov
• Abstract summary: The adoption of neural networks and deep learning in non-Euclidean domains has been hindered until recently by the lack of scalable and efficient learning frameworks. We attempt to bridge this gap by proposing ManOpt, a Python library for optimization on Riemannian in terms of machine learning models. The library is designed with the aim for a seamless integration with the ecosystem, targeting not only research, but also streamlining production machine learning pipelines.
• Score: 0.3655021726150367
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The adoption of neural networks and deep learning in non-Euclidean domains has been hindered until recently by the lack of scalable and efficient learning frameworks. Existing toolboxes in this space were mainly motivated by research and education use cases, whereas practical aspects, such as deploying and maintaining machine learning models, were often overlooked. We attempt to bridge this gap by proposing TensorFlow ManOpt, a Python library for optimization on Riemannian manifolds in TensorFlow. The library is designed with the aim for a seamless integration with the TensorFlow ecosystem, targeting not only research, but also streamlining production machine learning pipelines.

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