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global minimum
This term is primarily used in mathematics, computer science, and optimization theory. It describes the absolute lowest point of a function, distinguishing it from a local minimum, which is only the lowest point within a specific neighborhood or region of the domain.
In practical application, finding the global minimum is often the primary goal of machine learning training, such as minimizing a loss function. However, because many complex functions have multiple valleys, algorithms may accidentally settle in a local minimum, failing to reach the true global minimum.