activity
20192021
most citedPractical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

20 citations · 39 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

6 papers · 1 filter

cs.LG2021

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…

cs.LG2021

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…

cs.LG202118 cited

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

Ren Wang, Kaidi Xu, Sijia Liu +4

Model-agnostic meta-learning (MAML) has emerged as one of the most successful meta-learning techniques in few-shot learning. It enables us to learn a meta-initialization} of model…

cs.LG2020

RAILS: A Robust Adversarial Immune-inspired Learning System

Ren Wang, Tianqi Chen, Stephen Lindsly +3

Adversarial attacks against deep neural networks are continuously evolving. Without effective defenses, they can lead to catastrophic failure. The long-standing and arguably most p…

cs.LG202020 cited

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

Ren Wang, Gaoyuan Zhang, Sijia Liu +3

When the training data are maliciously tampered, the predictions of the acquired deep neural network (DNN) can be manipulated by an adversary known as the Trojan attack (or poisoni…

cs.LG2019

Tensor Recovery from Noisy and Multi-Level Quantized Measurements

Ren Wang, Meng Wang, Jinjun Xiong

Higher-order tensors can represent scores in a rating system, frames in a video, and images of the same subject. In practice, the measurements are often highly quantized due to the…