367 citations · 1.3k across the 62 of their papers we have counts for
8 papers · 1 filter
What it Thinks is Important is Important: Robustness Transfers through Input Gradients
Alvin Chan, Yi Tay, Yew-Soon Ong
Adversarial perturbations are imperceptible changes to input pixels that can change the prediction of deep learning models. Learned weights of models robust to such perturbations a…
Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks
Alvin Chan, Yew-Soon Ong
Deep learning models have recently shown to be vulnerable to backdoor poisoning, an insidious attack where the victim model predicts clean images correctly but classifies the same…
A Multi-Task Gradient Descent Method for Multi-Label Learning
Lu Bai, Yew-Soon Ong, Tiantian He +1
Multi-label learning studies the problem where an instance is associated with a set of labels. By treating single-label learning problem as one task, the multi-label learning probl…
Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy
Xinghua Qu, Zhu Sun, Yew-Soon Ong +2
Recent studies have revealed that neural network-based policies can be easily fooled by adversarial examples. However, while most prior works analyze the effects of perturbing ever…
DEVDAN: Deep Evolving Denoising Autoencoder
Andri Ashfahani, Mahardhika Pratama, Edwin Lughofer +1
The Denoising Autoencoder (DAE) enhances the flexibility of the data stream method in exploiting unlabeled samples. Nonetheless, the feasibility of DAE for data stream analytic des…
Automatic Construction of Multi-layer Perceptron Network from Streaming Examples
Mahardhika Pratama, Choiru Za'in, Andri Ashfahani +2
Autonomous construction of deep neural network (DNNs) is desired for data streams because it potentially offers two advantages: proper model's capacity and quick reaction to drift…
Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods
Haitao Liu, Yew-Soon Ong, Ziwei Yu +2
Gaussian process classification (GPC) provides a flexible and powerful statistical framework describing joint distributions over function space. Conventional GPCs however suffer fr…
AIR5: Five Pillars of Artificial Intelligence Research
Yew-Soon Ong, Abhishek Gupta
In this article, we provide and overview of what we consider to be some of the most pressing research questions facing the fields of artificial intelligence (AI) and computational…