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Solution: Non-Convex Optimization

Explore advanced gradient descent techniques for non-convex optimization problems. Learn to implement the Adam algorithm to escape local optima and adapt learning rates, enabling more effective optimization using NumPy.

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Explanation

The objective function is given as follows:

where a,b,c,dRa,b,c,d \in \R .

The partial derivatives of the objective function with respect to ...