Error-correcting semi-supervised pattern recognition with mode filter on graphs

Weiwei Du, Kiichi Urahama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A robust semi-supervised method using the mode filter has been presented for learning with partially-labeled training data including label errors. The mode filter has been originally developed for smoothing images contaminated with impulsive noises. However it needs nonlinear optimization which is usually solved with iterative methods. In this paper, we propose a direct solution method with full search of solution spaces. This direct method outperforms the iterative algorithm in classification rates and computational speeds. Additional iterations of the mode filter raise up the classification rates. We extend the mode filter by introducing weights based on the isolation degree of data, and show the effectiveness of this extension.

Original languageEnglish
Title of host publication2010 2nd International Symposium on Aware Computing, ISAC 2010 - Symposium Guide
Pages6-11
Number of pages6
DOIs
Publication statusPublished - 2010
Event2010 2nd International Symposium on Aware Computing, ISAC 2010 - Sapporo, Japan
Duration: Nov 1 2010Nov 4 2010

Other

Other2010 2nd International Symposium on Aware Computing, ISAC 2010
CountryJapan
CitySapporo
Period11/1/1011/4/10

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications

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  • Cite this

    Du, W., & Urahama, K. (2010). Error-correcting semi-supervised pattern recognition with mode filter on graphs. In 2010 2nd International Symposium on Aware Computing, ISAC 2010 - Symposium Guide (pp. 6-11). [5670502] https://doi.org/10.1109/ISAC.2010.5670502