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

20 citations · 51 across the 5 of their papers we have counts for

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5 papers

cs.LG2021★ 2 cited

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks

Shuai Zhang, Meng Wang, Sijia Liu +2

The \textit{lottery ticket hypothesis} (LTH) states that learning on a properly pruned network (the \textit{winning ticket}) improves test accuracy over the original unpruned netwo…

cs.LG2021★ 18 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★ 20 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.LG2020★ 7 cited

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

Shuai Zhang, Meng Wang, Sijia Liu +2

Although graph neural networks (GNNs) have made great progress recently on learning from graph-structured data in practice, their theoretical guarantee on generalizability remains…

cs.LG2019★ 4 cited

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…