Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints

Algorithm-dependent generalization error bounds are central to statistical learning theory. A learning algorithm may use a large hypothesis space, but the limited number of iterations controls its model capacity and generalization error. The impacts of stochastic gradient methods on generalization e...

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Hauptverfasser:	Mou, Wenlong, Wang, Liwei, Zhai, Xiyu, Zheng, Kai
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Mathematics - Optimization and Control Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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