Local minima refer to points in a function where the value is lower than that of its neighboring points, making it a candidate for optimization problems. These points are crucial because they can represent the best solution within a limited region, although not necessarily the overall best solution across the entire domain. Recognizing local minima is important in various optimization techniques, as they guide the convergence process and influence the effectiveness of algorithms used for finding optimal solutions.
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