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Data-Dependent Path Normalization in Neural Networks

Published 20 Nov 2015 in cs.LG | (1511.06747v4)

Abstract: We propose a unified framework for neural net normalization, regularization and optimization, which includes Path-SGD and Batch-Normalization and interpolates between them across two different dimensions. Through this framework we investigate issue of invariance of the optimization, data dependence and the connection with natural gradients.

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