Query by committee, linear separation and random walks

Shai Fine*, Ran Gilad-Bachrach, Eli Shamir

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

26 Scopus citations

Abstract

The problems involved in the implementation of machine learning by minimizing sample-complexity were studied. These problems were solved in the field of computational geometry based on random walks. A connection between random walks and machine learning notations such as support vector machines was also investigated.

Original languageEnglish
Pages (from-to)25-51
Number of pages27
JournalTheoretical Computer Science
Volume284
Issue number1
DOIs
StatePublished - 6 Jul 2002
EventComputing Learining Theory - Nordkirchen, Germany
Duration: 29 Mar 199931 Mar 1999

Keywords

  • Active learning
  • Experimental design
  • Labeled and unlabelled data
  • Selective sampling
  • Volume approximation

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