142 citations · 340 across the 10 of their papers we have counts for
11 papers
Scalable Whitebox Attacks on Tree-based Models
Giuseppe Castiglione, Gavin Ding, Masoud Hashemi +2
Adversarial robustness is one of the essential safety criteria for guaranteeing the reliability of machine learning models. While various adversarial robustness testing approaches…
CDT: Cascading Decision Trees for Explainable Reinforcement Learning
Zihan Ding, Pablo Hernandez-Leal, Gavin Weiguang Ding +2
Deep Reinforcement Learning (DRL) has recently achieved significant advances in various domains. However, explaining the policy of RL agents still remains an open problem due to se…
Cascaded Deep Neural Networks for Retinal Layer Segmentation of Optical Coherence Tomography with Fluid Presence
Donghuan Lu, Morgan Heisler, Da Ma +5
Optical coherence tomography (OCT) is a non-invasive imaging technology which can provide micrometer-resolution cross-sectional images of the inner structures of the eye. It is wid…
On the Effectiveness of Low Frequency Perturbations
Yash Sharma, Gavin Weiguang Ding, Marcus Brubaker
Carefully crafted, often imperceptible, adversarial perturbations have been shown to cause state-of-the-art models to yield extremely inaccurate outputs, rendering them unsuitable…
On the Sensitivity of Adversarial Robustness to Input Data Distributions
Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin +2
Neural networks are vulnerable to small adversarial perturbations. Existing literature largely focused on understanding and mitigating the vulnerability of learned models. In this…
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch
Gavin Weiguang Ding, Luyu Wang, Xiaomeng Jin
advertorch is a toolbox for adversarial robustness research. It contains various implementations for attacks, defenses and robust training methods. advertorch is built on PyTorch (…