Siyue Wang | DeepAI

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Featured Co-authors

Chang Liu
231 publications
Pin-Yu Chen
183 publications
Xiao Wang
144 publications
Liang Zhao
139 publications
Jian Tang
129 publications
Yanzhi Wang
123 publications
Bo Yuan
72 publications
Caiwen Ding
68 publications
Yifan Gong
59 publications
Xue Lin
57 publications
DingDingwen Tao
39 publications

∙ 03/27/2023

EMShepherd: Detecting Adversarial Samples via Side-channel Leakage

Deep Neural Networks (DNN) are vulnerable to adversarial perturbations-s...

0 Ruyi Ding, et al. ∙

∙ 05/14/2021

High-Robustness, Low-Transferability Fingerprinting of Neural Networks

This paper proposes Characteristic Examples for effectively fingerprinti...

0 Siyue Wang, et al. ∙

∙ 02/19/2020

AdvMS: A Multi-source Multi-cost Defense Against Adversarial Attacks

Designing effective defense against adversarial attacks is a crucial top...

15 Xiao Wang, et al. ∙

∙ 02/19/2020

RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition

Recurrent neural networks (RNNs) based automatic speech recognition has ...

0 Peiyan Dong, et al. ∙

∙ 02/18/2020

Block Switching: A Stochastic Approach for Deep Learning Security

Recent study of adversarial attacks has revealed the vulnerability of mo...

8 Xiao Wang, et al. ∙

∙ 02/18/2020

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

Despite the great achievements of the modern deep neural networks (DNNs)...

25 Pu Zhao, et al. ∙

∙ 08/20/2019

Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses

Despite achieving remarkable success in various domains, recent studies ...

4 Xiao Wang, et al. ∙

∙ 05/28/2019

Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks

Despite the great achievements of deep neural networks (DNNs), the vulne...

0 Pu Zhao, et al. ∙

∙ 12/12/2018

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Recurrent Neural Networks (RNNs) are becoming increasingly important for...

0 Zhe Li, et al. ∙

∙ 09/13/2018

Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks

Deep neural networks (DNNs) are known vulnerable to adversarial attacks....

0 Siyue Wang, et al. ∙

∙ 03/14/2018

On the Universal Approximation Property and Equivalence of Stochastic Computing-based Neural Networks and Binary Neural Networks

Large-scale deep neural networks are both memory intensive and computati...

0 Yanzhi Wang, et al. ∙

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