128 citations · 249 across the 11 of their papers we have counts for
11 papers
NP-Hardness of Tensor Network Contraction Ordering
Jianyu Xu, Hanwen Zhang, Ling Liang +3
We study the optimal order (or sequence) of contracting a tensor network with a minimal computational cost. We conclude 2 different versions of this optimal sequence: that minimize…
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…
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks
Ling Liang, Zheng Qu, Zhaodong Chen +6
Although spiking neural networks (SNNs) take benefits from the bio-plausible neural modeling, the low accuracy under the common local synaptic plasticity learning rules limits thei…
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…