28 citations · 44 across the 9 of their papers we have counts for
9 papers
Recurrent Attention Networks for Long-text Modeling
Xianming Li, Zongxi Li, Xiaotian Luo +5
Self-attention-based models have achieved remarkable progress in short-text mining. However, the quadratic computational complexities restrict their application in long text proces…
Model-Agnostic Reachability Analysis on Deep Neural Networks
Chi Zhang, Wenjie Ruan, Fu Wang +3
Verification plays an essential role in the formal analysis of safety-critical systems. Most current verification methods have specific requirements when working on Deep Neural Net…
Towards Verifying the Geometric Robustness of Large-scale Neural Networks
Fu Wang, Peipei Xu, Wenjie Ruan +1
Deep neural networks (DNNs) are known to be vulnerable to adversarial geometric transformation. This paper aims to verify the robustness of large-scale DNNs against the combination…
How and what to learn:The modes of machine learning
Sihan Feng, Yong Zhang, Fuming Wang +1
Despite their great success, neural networks still remain as black-boxes due to the lack of interpretability. Here we propose a new analyzing method, namely the weight pathway anal…
Topic Driven Adaptive Network for Cross-Domain Sentiment Classification
Yicheng Zhu, Yiqiao Qiu, Qingyuan Wu +2
Cross-domain sentiment classification has been a hot spot these years, which aims to learn a reliable classifier using labeled data from a source domain and evaluate it on a target…
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude
Fu Wang, Yanghao Zhang, Yanbin Zheng +1
Adversarial training is an effective but time-consuming way to train robust deep neural networks that can withstand strong adversarial attacks. As a response to its inefficiency, w…
Fooling Object Detectors: Adversarial Attacks by Half-Neighbor Masks
Yanghao Zhang, Fu Wang, Wenjie Ruan
Although there are a great number of adversarial attacks on deep learning based classifiers, how to attack object detection systems has been rarely studied. In this paper, we propo…
Generalizing Universal Adversarial Attacks Beyond Additive Perturbations
Yanghao Zhang, Wenjie Ruan, Fu Wang +1
The previous study has shown that universal adversarial attacks can fool deep neural networks over a large set of input images with a single human-invisible perturbation. However,…
SDN-controlled and Orchestrated OPSquare DCN Enabling Automatic Network Slicing with Differentiated QoS Provisioning
Xuwei Xue, Fu Wang, Fernando Agraz +6
In this work, we propose and experimentally assess the automatic and flexible NSs configurations of optical OPSquare DCN controlled and orchestrated by an extended SDN control plan…