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What is Loss Landscape Analysis of Neural Networks about?

This document presents a novel class of functions characterized by the α-β-condition, which allows for the analysis of the loss landscape of neural networks without requiring extensive over-parametrization. The authors demonstrate that gradient-based optimizers can converge under this condition, providing both theoretical guarantees and empirical validation across various deep learning models. The work addresses limitations of existing conditions like Polyak-Łojasiewicz and Aiming, which often necessitate i

Author

chant28

Language

EN