Acceleration techniques for the network inversion algorithm

Hiroyuki Takizawa, Taira Nakajimat, Masaaki Nishi, Hiroaki Kobayashi, Tadao Nakamura

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

We apply two acceleration techniques for the backpropagation algorithm to an iterative gradient descent algorithm called the network inversion algorithm. Experimental results show that these techniques are also quite effective to decrease the number of iterations required for the detection of input vectors on the classification boundary of a multilayer perceptron.

Original languageEnglish
Pages (from-to)508-511
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE82-D
Issue number2
Publication statusPublished - 1999 Jan 1

Keywords

  • Active learning based on existing training examples
  • Classification problems
  • Multilayer perceptrons
  • The network inversion algorithm

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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