What is the difference between local minima and global minima in optimization?
An example of an AI chatbot conversation about local minima vs global minima in optimization.
What is the difference between local minima and global minima in optimization?
In optimization, a local minimum is a point where the function value is lower than its neighbors, while a global minimum is the lowest point in the entire function.
Can you give an example of each?
Sure! Imagine a hilly landscape: a local minimum is like a small valley, while the global minimum is the deepest valley in the entire landscape.
Why is it important to distinguish between them?
Distinguishing between them is crucial because optimization algorithms may get stuck in local minima, preventing them from finding the best solution.
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