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Non-Singularity of the Gradient Descent map for Neural Networks with Piecewise Analytic Activations
The theory of training deep networks has become a central question of modern machine learning and has inspired many practical advancements. In particular, the gradient descent (GD) optimization algorithm has been extensively studied in recent years. A key assumption about GD has appeared in several
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