Stretchy multivariate polynomial classification

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

2 Citations (Scopus)

Abstract

A stretchy classification methodology adopting multivariate polynomials is proposed in this paper. Through minimization of an approximated p-norm of the parameter vector subject to classification error constraints, an approximated minimum norm solution in dual form is derived for under-determined systems. This is subsequently transformed into its primal form for over-determined systems. Practical feasibility of the proposed solution is illustrated by an evaluation on synthetic data as well as an application on benchmark real-world data.

Original languageEnglish
Title of host publication2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479980550
DOIs
Publication statusPublished - 2015 May 13
Event10th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015 - Singapore, Singapore
Duration: 2015 Apr 72015 Apr 9

Publication series

Name2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015

Other

Other10th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015
Country/TerritorySingapore
CitySingapore
Period15/4/715/4/9

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Information Systems

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