@ARTICLE{
author={Anderberg Alastair,Bailey James,Campello Ricardo JGB,Houle Michael E,Marques Henrique O,Radovanovic Milos S,Zimek Arthur},
year={2024},
title={Dimensionality-Aware Outlier Detection},
journal={PROCEEDINGS OF THE 2024 SIAM INTERNATIONAL CONFERENCE ON DATA MINING, SDM},
volume={},
number={},
pages={652-660},
document_type={Proceedings Paper},
} 

@ARTICLE{
author={Amsaleg Laurent,Bailey James A,Barbe Amdeie,Erfani Sarah M,Furon Teddy,Houle Michael E,Radovanovic Milos M,Xuan Vinh Nguyen},
year={2021},
title={High Intrinsic Dimensionality Facilitates Adversarial Attack: Theoretical Evidence},
journal={IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY},
volume={16},
number={},
pages={854-865},
document_type={Article},
} 

@ARTICLE{
author={Bratic Brankica,Houle Michael E,Kurbalija Vladimir M,Oria Vincent,Radovanovic Milos M},
year={2019},
title={The Influence of Hubness on NN-Descent},
journal={INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS},
volume={28},
number={6},
pages={-},
document_type={Article},
} 

@ARTICLE{
author={Amsaleg Laurent,Bailey James A,Barbe Dominique,Erfani Sarah M,Houle Michael E,Vinh Nguyen,Radovanovic Milos M},
year={2017},
title={The Vulnerability of Learning to Adversarial Perturbation Increases with Intrinsic Dimensionality},
journal={2017 IEEE WORKSHOP ON INFORMATION FORENSICS AND SECURITY (WIFS)},
volume={},
number={},
pages={-},
document_type={Proceedings Paper},
}