Robust datamining

Uwe, Aickelin

Abstract

Our long-term research goal is to develop datamining methodologies that are robust to changes in data and uncertainty. By robust we mean solutions remain ‘optimal’ when things change or are easily repaired. Broadly, this robustness can be achieved in two ways: One, by having ‘slack’ in the solution or two, by constructing the solution such that is easily repairable, e.g. failures are isolated.

Citation

Uwe, A. (2017). Robust datamining.

• Conference Name: 4th Asia Pacific Conference on Advanced Research (APCAR - Mar, 2017)
• End Date: Mar 5, 2017
• Acceptance Date: Feb 1, 2017
• Publication Date: Mar 5, 2017
• Deposit Date: Nov 15, 2017
• Publicly Available Date: Nov 15, 2017
• Journal: 4th Asia Pacific Conference on Advanced Research (APCAR- MAR 2017), Melbourne, Australia
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/848679
• Related Public URLs: http://apiar.org.au/?conference=4th-asia-pacific-conference-on-advanced-research-apcar-mar-2017-melbourne-australia
• Additional Information: Proceedings published by Asia Pacific Institute of Advanced Research. ISBN 9780995398009 / ISSN 2207-2799