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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.02167 |
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| _version_ | 1866913295907160064 |
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| author | Wang, Adam |
| author_facet | Wang, Adam |
| contents | The following note proves that conditional entropy of a sequence is almost time-reversal invariant, specifically they only differ by a small constant factor dependent only upon the forward and backward models that the entropies are being calculated with respect to. This gives rise to a numerical value that quantifies learnability, as well as a methodology to control for distributional shift between datasets. Rough guidelines are given for practitioners. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_02167 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A remark on conditional entropy Wang, Adam Information Theory The following note proves that conditional entropy of a sequence is almost time-reversal invariant, specifically they only differ by a small constant factor dependent only upon the forward and backward models that the entropies are being calculated with respect to. This gives rise to a numerical value that quantifies learnability, as well as a methodology to control for distributional shift between datasets. Rough guidelines are given for practitioners. |
| title | A remark on conditional entropy |
| topic | Information Theory |
| url | https://arxiv.org/abs/2404.02167 |