The EM Algorithm in Information Geometry
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917701427920896 |
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| author | Suliman, Sammy |
| author_facet | Suliman, Sammy |
| contents | The purpose of this thesis is to convey the basic concepts of information geometry and its applications to non-specialists and those in applied fields, assuming only a first-year undergraduate background in calculus, linear algebra, and probability theory / statistics. We first begin with an introduction to the EM algorithm, providing a typical use case in Python, before moving to an overview of basic Riemannian geometry. We then introduce the core concepts of information geometry and the $em$ algorithm, with an explicit calculation of both the $e$ and $m$ projection, before closing with a discussion of an important application of this research to the field of deep learning, providing a novel implementation in Python. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_15398 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The EM Algorithm in Information Geometry Suliman, Sammy History and Overview Information Theory The purpose of this thesis is to convey the basic concepts of information geometry and its applications to non-specialists and those in applied fields, assuming only a first-year undergraduate background in calculus, linear algebra, and probability theory / statistics. We first begin with an introduction to the EM algorithm, providing a typical use case in Python, before moving to an overview of basic Riemannian geometry. We then introduce the core concepts of information geometry and the $em$ algorithm, with an explicit calculation of both the $e$ and $m$ projection, before closing with a discussion of an important application of this research to the field of deep learning, providing a novel implementation in Python. |
| title | The EM Algorithm in Information Geometry |
| topic | History and Overview Information Theory |
| url | https://arxiv.org/abs/2406.15398 |