Finite Sample and Large Deviations Analysis of Stochastic Gradient Algorithm with Correlated Noise
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913541782503424 |
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| author | Yin, George Krishnamurthy, Vikram |
| author_facet | Yin, George Krishnamurthy, Vikram |
| contents | We analyze the finite sample regret of a decreasing step size stochastic gradient algorithm. We assume correlated noise and use a perturbed Lyapunov function as a systematic approach for the analysis. Finally we analyze the escape time of the iterates using large deviations theory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_08449 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Finite Sample and Large Deviations Analysis of Stochastic Gradient Algorithm with Correlated Noise Yin, George Krishnamurthy, Vikram Machine Learning Systems and Control We analyze the finite sample regret of a decreasing step size stochastic gradient algorithm. We assume correlated noise and use a perturbed Lyapunov function as a systematic approach for the analysis. Finally we analyze the escape time of the iterates using large deviations theory. |
| title | Finite Sample and Large Deviations Analysis of Stochastic Gradient Algorithm with Correlated Noise |
| topic | Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2410.08449 |