61 citations · 116 across the 8 of their papers we have counts for
14 papers
Toward Robust Spiking Neural Network Against Adversarial Perturbation
Ling Liang, Kaidi Xu, Xing Hu +2
As spiking neural networks (SNNs) are deployed increasingly in real-world efficiency critical applications, the security concerns in SNNs attract more attention. Currently, researc…
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Husheng Han, Kaidi Xu, Xing Hu +6
Adversarial patch attacks that craft the pixels in a confined region of the input images show their powerful attack effectiveness in physical environments even with noises or defor…
Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment
Jiaming Guo, Rui Zhang, Xishan Zhang +6
Policy gradient methods are appealing in deep reinforcement learning but suffer from high variance of gradient estimate. To reduce the variance, the state value function is applied…
Rubik: A Hierarchical Architecture for Efficient Graph Learning
Xiaobing Chen, Yuke Wang, Xinfeng Xie +9
Graph convolutional network (GCN) emerges as a promising direction to learn the inductive representation in graph data commonly used in widespread applications, such as E-commerce,…
SEALing Neural Network Models in Secure Deep Learning Accelerators
Pengfei Zuo, Yu Hua, Ling Liang +3
Deep learning (DL) accelerators are increasingly deployed on edge devices to support fast local inferences. However, they suffer from a new security problem, i.e., being vulnerable…
HyGCN: A GCN Accelerator with Hybrid Architecture
Mingyu Yan, Lei Deng, Xing Hu +6
In this work, we first characterize the hybrid execution patterns of GCNs on Intel Xeon CPU. Guided by the characterization, we design a GCN accelerator, HyGCN, using a hybrid arch…