A Generalized Bias-Variance Decomposition for Bregman Divergences
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914152748941312 |
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| author | Pfau, David |
| author_facet | Pfau, David |
| contents | The bias-variance decomposition is a central result in statistics and machine learning, but is typically presented only for the squared error. We present a generalization of the bias-variance decomposition where the prediction error is a Bregman divergence, which is relevant to maximum likelihood estimation with exponential families. While the result is already known, there was not previously a clear, standalone derivation, so we provide one for pedagogical purposes. A version of this note previously appeared on the author's personal website without context. Here we provide additional discussion and references to the relevant prior literature. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_08789 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Generalized Bias-Variance Decomposition for Bregman Divergences Pfau, David Machine Learning The bias-variance decomposition is a central result in statistics and machine learning, but is typically presented only for the squared error. We present a generalization of the bias-variance decomposition where the prediction error is a Bregman divergence, which is relevant to maximum likelihood estimation with exponential families. While the result is already known, there was not previously a clear, standalone derivation, so we provide one for pedagogical purposes. A version of this note previously appeared on the author's personal website without context. Here we provide additional discussion and references to the relevant prior literature. |
| title | A Generalized Bias-Variance Decomposition for Bregman Divergences |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2511.08789 |