6 citations · 6 across the 1 of their papers we have counts for
4 papers
IDT: Dual-Task Adversarial Attacks for Privacy Protection
Pedro Faustini, Shakila Mahjabin Tonni, Annabelle McIver +2
Natural language processing (NLP) models may leak private information in different ways, including membership inference, reconstruction or attribute inference attacks. Sensitive in…
Bayes' capacity as a measure for reconstruction attacks in federated learning
Sayan Biswas, Mark Dras, Pedro Faustini +4
Within the machine learning community, reconstruction attacks are a principal attack of concern and have been identified even in federated learning, which was designed with privacy…
What Learned Representations and Influence Functions Can Tell Us About Adversarial Examples
Shakila Mahjabin Tonni, Mark Dras
Adversarial examples, deliberately crafted using small perturbations to fool deep neural networks, were first studied in image processing and more recently in NLP. While approaches…
An empirical study for Vietnamese dependency parsing
Dat Quoc Nguyen, Mark Dras, Mark Johnson
This paper presents an empirical comparison of different dependency parsers for Vietnamese, which has some unusual characteristics such as copula drop and verb serialization. Exper…