Query-by-committee improvement with diversity and density in batch active learning-Reference-Cited by-同舟云学术

Query-by-committee improvement with diversity and density in batch active learning

Published:2018-07 Issue: Volume:454-455 Page:401-418
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Kee Seho^ORCID,del Castillo Enrique,Runger George

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

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