Interactive Machine Learning with the “human-in-the-loop”

Holzinger, A. (Participant)

Institute of Interactive Systems and Data Science (7060)

Activity: Participation in or organisation of › Workshop, seminar or course (Participation in/Organisation of)

Period	1 Sept 2015
Event type	Conference
Location	London, United KingdomShow on map

Keywords

Machine Learning
Health Informatics

ASJC Scopus subject areas

Artificial Intelligence

Fields of Expertise

Information, Communication & Computing

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)
Application
Experimental

Documents & Links

Sometimes we do not have big data – but complex data. Applying fully automatic machine learning methods might – when lacking training samples result in artefacts. In this case interactive machine learning may help by putting the human-into-the-loop of the algorithms and benefit from the power of human cognition. This can be particularly beneficial when dealing with NP-hard problems. Examples include subspace clustering, k-anonymization or protein folding – just to name some cases.

Related content

Publications
An Adaptive Annotation Approach for Biomedical Entity and Relation Recognition
Research output: Contribution to journal › Article › peer-review
Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Fuzzy Image Processing
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review