Summary of Pybregman: a Python Library For Bregman Manifolds, by Frank Nielsen and Alexander Soen
pyBregMan: A Python library for Bregman Manifolds
by Frank Nielsen, Alexander Soen
First submitted to arxiv on: 8 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computational Geometry (cs.CG); Computer Vision and Pattern Recognition (cs.CV); Information Theory (cs.IT)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a library called pyBregMan that implements generic operations on Bregman manifolds, which are induced by smooth strictly convex functions. The library instantiates several common Bregman manifolds used in information sciences, including the Fisher-Rao manifolds of categorical/multinomial distributions and multivariate normal distributions. The core of the library is based on Legendre-Fenchel duality, which induces a canonical pair of dual potential functions and dual Bregman divergences. The library also provides several core algorithms for various applications in statistics, machine learning, information fusion, and so on. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a tool called pyBregMan that helps with some mathematical concepts used in science and technology. It’s like a toolbox that makes it easier to work with certain types of math problems. The tool can be used for things like studying patterns in data, making predictions, and combining information from different sources. |
Keywords
» Artificial intelligence » Machine learning
