Convergence of the EM algorithm via proximal techniques
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Accesso online: | |
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| _version_ | 1866915708795879424 |
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| author | Noll, Dominikus |
| author_facet | Noll, Dominikus |
| contents | We investigate convergence of the expectation maximization algorithm by representing it as a generalized proximal method. Convergence of iterates and not just in value is investigated under natural hypotheses such as definability of the incomplete data log-likelihood in the sense of o-minimal structure theory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_02252 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Convergence of the EM algorithm via proximal techniques Noll, Dominikus Statistics Theory 65K05 49J52 62D10 62B11 We investigate convergence of the expectation maximization algorithm by representing it as a generalized proximal method. Convergence of iterates and not just in value is investigated under natural hypotheses such as definability of the incomplete data log-likelihood in the sense of o-minimal structure theory. |
| title | Convergence of the EM algorithm via proximal techniques |
| topic | Statistics Theory 65K05 49J52 62D10 62B11 |
| url | https://arxiv.org/abs/2601.02252 |