ROAST selectively trains anomaly detectors on less vulnerable patient data with targeted outlier exposure, boosting recall by 16.2% in black-box settings and reducing training time by 88.3%.
Machine learning with electronic health records is vulnerable to backdoor trigger attacks.arXiv preprint arXiv:2106.07925, 2021
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks
ROAST selectively trains anomaly detectors on less vulnerable patient data with targeted outlier exposure, boosting recall by 16.2% in black-box settings and reducing training time by 88.3%.