Active Learning with Unsupervised Ensembles of Classifiers

ICASSP 2020
Pages: 3967 - 3971
Published: May 4, 2020
Abstract
The present work introduces a simple scheme for active classification of data using unsupervised ensembles of classifiers. Uncertainty sampling, with different uncertainty measures, is evaluated for data selection, while an online expectation maximization algorithm is derived to estimate model parameters on-the-fly. Preliminary tests on real data showcase the potential of the novel...
Paper Details
Title
Active Learning with Unsupervised Ensembles of Classifiers
DOI
Published Date
May 4, 2020
Journal
Pages
3967 - 3971
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.