Gradient Descent Can Theoretically Reproduce Any Weight-Finding Algorithm
August 19, 2026
Any algorithm capable of finding optimal network weights for classification can be matched by an extended network trainable via gradient descent. The construction serves as a theoretical framework for understanding the limits of meta-learning rather than a practical implementation method.
HOW THIS AFFECTS YOU
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researcherYou can use this theoretical bound to orient meta-learning research toward architectures that are inherently optimizable via gradient descent.