Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization

30 Jun 2020Rie JohnsonTong Zhang

This paper presents a framework of successive functional gradient optimization for training nonconvex models such as neural networks, where training is driven by mirror descent in a function space. We provide a theoretical analysis and empirical study of the training method derived from this framework... (read more)

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