A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality

Adaptive gradient-descent optimizers are the standard choice for training neural network models. Despite their faster convergence than gradient-descent and remarkable performance in practice, the adaptive optimizers are not as well understood as vanilla gradient-descent. A reason is that the dynamic...

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Hauptverfasser:	Chakrabarti, Kushal, Baranwal, Mayank
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Mathematics - Optimization and Control Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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