
The uncertainty inherent in real-world data and the permutative redundancy of deep learning architectures pose significant challenges to traditional gradient-based optimization methods, potentially hindering the efficient training and generalization of deep learning models.


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the-impact-of-objective-function-uncertainty-and-permutative-redundancy-on-deep-learning-optimization


The Impact of Objective Function Uncertainty and Permutative Redundancy on Deep Learning Optimization
