Statistics Sequential statistics Concept
Robbins–Monro algorithm
Summary
The Robbins–Monro algorithm is the first stochastic approximation method, introduced by Herbert Robbins and Sutton Monro in 1951. It finds the point where an increasing function, observed only through noisy measurements, takes a given value. It updates the current guess by a step proportional to the observed error, with step sizes that shrink at a suitable rate.
Further reading
- Web https://en.wikipedia.org/wiki/Stochastic_approximation, Robbins–Monro algorithm
About this page
| Tag | CHHD44WDHJ |
|---|---|
| URI | m2://CHHD44WDHJ |
| Kind | concept |
| Writing | W0 stub |
| MSC | 62L20 |
| Specializes | Stochastic approximation |
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