Multi Source Inference From Heterogeneous Dynamic Networks

High intrinsic dimensionality facilitates adversarial attack: Theoretical evidence

L Amsaleg, J Bailey, A Barbe, SM Erfani, T Furon, ME Houle, M Radovanovic, XV Nguyen

2021-01-01

Machine learning systems are vulnerable to adversarial attack. By applying to the input object a small, carefully-designed perturb..

The vulnerability of learning to adversarial perturbation increases with intrinsic dimensionality

L Amsaleg, J Bailey, D Barbe, S Erfani, ME Houle, V Nguyen, M Radovanovic

2018-01-23

© 2017 IEEE. Recent research has shown that machine learning systems, including state-of-the-art deep neural networks, are vulnera..

Discovering outlying aspects in large datasets

NX Vinh, J Chan, S Romano, J Bailey, C Leckie, K Ramamohanarao, J Pei

2016-11-01

We address the problem of outlying aspects mining: given a query object and a reference multidimensional data set, how can we disc..

Training Robust Models with Random Projection

XV Nguyen, S Monazam Erfani, S Paisitkriangkrai, J Bailey, C Leckie, K Ramamohanarao

2016-01-01

Regularization plays an important role in machine learning systems. We propose a novel methodology for model regularization using ..

Detection of Deception in the Mafia Party Game

S Demyanov, J Bailey, R Kotagiri, C Leckie

2015-01-01

The problem of deception detection is very challenging. Only trained people with specialist knowledge are able to demonstrate an a..