Dr Ehsan Toreini ehsan.toreini@durham.ac.uk
Academic Visitor
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
Toreini, Ehsan; Aitken, Mhairi; Coopamootoo, Kovila PL; Elliott, Karen; Zelaya, Vladimiro Gonzalez; Missier, Paolo; Ng, Magdalene; van Moorsel, Aad
Authors
Mhairi Aitken
Kovila PL Coopamootoo
Karen Elliott
Vladimiro Gonzalez Zelaya
Paolo Missier
Magdalene Ng
Aad van Moorsel
Citation
Toreini, E., Aitken, M., Coopamootoo, K. P., Elliott, K., Zelaya, V. G., Missier, P., Ng, M., & van Moorsel, A. (online). Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
| Journal Article Type | Article |
|---|---|
| Deposit Date | Sep 21, 2020 |
| Journal | arXiv preprint arXiv:2007.08911 |
| Public URL | https://durham-repository.worktribe.com/output/1261867 |
You might also like
How Can and Would People Protect From Online Tracking?
(2021)
Journal Article
Anti-Counterfeiting for Polymer Banknotes Based on Polymer Substrate Fingerprinting
(2021)
Journal Article
DOMtegrity: ensuring web page integrity against malicious browser extensions
(2019)
Journal Article
Stealing PINs via mobile sensors: actual risk versus user perception
(2018)
Journal Article
New advances in tamper evident technologies
(2018)
Thesis
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search