Reference : Predicting Vulnerability to Poverty with Machine Learning
Scientific congresses, symposiums and conference proceedings : Poster
Business & economic sciences : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/47572
Predicting Vulnerability to Poverty with Machine Learning
English
Taye, Alemayehu mailto [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) >]
d'Ambrosio, Conchita mailto [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) >]
21-May-2021
No
National
DTU DRIVEN Colloquium
21/05/2021
Andreas Zilian
University of Luxembourg
Luxembourg
[en] Machine Learning ; Vulnerability ; Poverty ; Wellbeing
Researchers
http://hdl.handle.net/10993/47572
FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Poster.pdfAuthor postprint248.52 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.