20 citations · 43 across the 11 of their papers we have counts for
11 papers
Bridging Models to Defend: A Population-Based Strategy for Robust Adversarial Defense
Ren Wang, Yuxuan Li, Can Chen +6
Adversarial robustness is a critical measure of a neural network's ability to withstand adversarial attacks at inference time. While robust training techniques have improved defens…
Towards Understanding How Self-training Tolerates Data Backdoor Poisoning
Soumyadeep Pal, Ren Wang, Yuguang Yao +1
Recent studies on backdoor attacks in model training have shown that polluting a small portion of training data is sufficient to produce incorrect manipulated predictions on poison…
Multi-Trigger-Key: Towards Multi-Task Privacy Preserving In Deep Learning
Ren Wang, Zhe Xu, Alfred Hero
Deep learning-based Multi-Task Classification (MTC) is widely used in applications like facial attributes and healthcare that warrant strong privacy guarantees. In this work, we ai…
Deep Adversarially-Enhanced k-Nearest Neighbors
Ren Wang, Tianqi Chen, Alfred Hero
Recent works have theoretically and empirically shown that deep neural networks (DNNs) have an inherent vulnerability to small perturbations. Applying the Deep k-Nearest Neighbors…
RAILS: A Robust Adversarial Immune-inspired Learning System
Ren Wang, Tianqi Chen, Stephen Lindsly +4
Adversarial attacks against deep neural networks (DNNs) are continuously evolving, requiring increasingly powerful defense strategies. We develop a novel adversarial defense framew…
Immuno-mimetic Deep Neural Networks (Immuno-Net)
Ren Wang, Tianqi Chen, Stephen Lindsly +3
Biomimetics has played a key role in the evolution of artificial neural networks. Thus far, in silico metaphors have been dominated by concepts from neuroscience and cognitive psyc…