An Error-Correcting Output Code Framework for Lifelong Learning without a Teacher

Shen Shyang Ho, Mathew Marchiano, Scott Zockoll, Hieu Nguyen

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

Abstract

An intelligent system should learn new concepts continuously and autonomously. The system should recognize that a concept is new and learn the concept without any guidance. In this paper, a novel error correcting output code (ECOC)-based framework, motivated by the complementary learning systems (CLS) theory, is proposed to perform (i) rapid detection of a new concept and (ii) learning and storing of the new concept via reinforced encoding. Experimental results on six datasets show the feasibility and competitive performance of the proposed ECOC-based framework for life-long learning using four different base classifiers against two baseline approaches. Moreover, we demonstrate the performance of our proposed ECOC-based framework on a continual learning scenario without any label feedback using a realistic but stringent cumulative performance measure, which combines detection error and classification error.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020
EditorsMiltos Alamaniotis, Shimei Pan
PublisherIEEE Computer Society
Pages249-254
Number of pages6
ISBN (Electronic)9781728192284
DOIs
StatePublished - Nov 2020
Event32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020 - Virtual, Baltimore, United States
Duration: Nov 9 2020Nov 11 2020

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2020-November
ISSN (Print)1082-3409

Conference

Conference32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020
CountryUnited States
CityVirtual, Baltimore
Period11/9/2011/11/20

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Computer Science Applications

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