Do gradient descent methods always converge to the same point?
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Answer / Mohammad Arman Ansari
No, gradient descent methods do not always converge to the same point. The final solution (minimum) of a cost function depends on the initial conditions (initial weights or parameters). Different initial conditions can lead to different local minima (points where the gradient is zero or close to zero), and some of these may not be the global minimum (the lowest possible value of the cost function for that problem).
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