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

Weiwei Du, Kiichi Urahama

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

    4 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

    Publication series

    Name2010 2nd International Symposium on Aware Computing, ISAC 2010 - Symposium Guide

    Other

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

    All Science Journal Classification (ASJC) codes

    • Computational Theory and Mathematics
    • Computer Science Applications

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