78 citations · 83 across the 8 of their papers we have counts for
8 papers
Defending Distributed Classifiers Against Data Poisoning Attacks
Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani +1
Support Vector Machines (SVMs) are vulnerable to targeted training data manipulations such as poisoning attacks and label flips. By carefully manipulating a subset of training samp…
Defending Regression Learners Against Poisoning Attacks
Sandamal Weerasinghe, Sarah M. Erfani, Tansu Alpcan +2
Regression models, which are widely used from engineering applications to financial forecasting, are vulnerable to targeted malicious attacks such as training data poisoning, throu…
Graph Neural Networks with Continual Learning for Fake News Detection from Social Media
Yi Han, Shanika Karunasekera, Christopher Leckie
Although significant effort has been applied to fact-checking, the prevalence of fake news over social media, which has profound impact on justice, public trust and our society, re…
METEOR: Learning Memory and Time Efficient Representations from Multi-modal Data Streams
Amila Silva, Shanika Karunasekera, Christopher Leckie +1
Many learning tasks involve multi-modal data streams, where continuous data from different modes convey a comprehensive description about objects. A major challenge in this context…
Black-box Adversarial Example Generation with Normalizing Flows
Hadi M. Dolatabadi, Sarah Erfani, Christopher Leckie
Deep neural network classifiers suffer from adversarial vulnerability: well-crafted, unnoticeable changes to the input data can affect the classifier decision. In this regard, the…
Image Analysis Enhanced Event Detection from Geo-tagged Tweet Streams
Yi Han, Shanika Karunasekera, Christopher Leckie
Events detected from social media streams often include early signs of accidents, crimes or disasters. Therefore, they can be used by related parties for timely and efficient respo…