Lesson plan
Gradient method
In optimization, a gradient method is an algorithm to solve problems of the form : \min_{x\in\mathbb R^n}\; f(x) with the search directions defined by the gradient of the function at the current point. Examples of gradient methods are the gradient descent and the conjugate gradient.
Article summary
In optimization, a gradient method is an algorithm to solve problems of the form : \min_{x\in\mathbb R^n}\; f(x) with the search directions defined by the gradient of the function at the current point. Examples of gradient methods are the gradient descent and the conjugate gradient.
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.