Competitive Learning with Feedforward Supervisory Signal for Pre-trained Multilayered Networks

2013/12/20 by Takashi Shinozaki, Yasushi Naruse, Shinozaki, Takashi +1
Computer Science · Mathematics · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE) #cs.CV #cs.LG #cs.NE #stat.ML

paper · pdf · doi:10.48550/arxiv.1312.5845

This paper has been withdrawn by the author since the review process for the conference to which it was applied ended

arxiv created 2015/02/16 · arxiv updated 2015/02/17

Abstract

We propose a novel learning method for multilayered neural networks which uses feedforward supervisory signal and associates classification of a new input with that of pre-trained input. The proposed method effectively uses rich input information in the earlier layer for robust leaning and revising internal representation in a multilayer neural network.

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