基本信息
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个人简介
My latest work on deep learning security draws inspiration from the temporal computation found in spiking neural networks (SNN) to make having secure networks more accessible. State of the art techniques to train deep networks that are robust to adversarial examples - small, crafted perturbations to input images that fool networks with high confidence - are very computationally expensive and often require redundant neural networks and the injection of many additional training examples. Temporal computation promotes decision-making in deep neural networks that is more context driven and makes feature extraction more robust to small adversarial perturbations.
研究兴趣
论文共 8 篇作者统计合作学者相似作者
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arxiv(2024)
引用0浏览0引用
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CoRR (2024)
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Jingyang Zhang,Jingwei Sun ,Eric C. Yeats, Yang Ouyang,Martin Kuo,Jianyi Zhang, Hao Yang,Hai Helen Li
CoRR (2024)
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CoRR (2023)
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ICLR 2023 (2023)
European Conference on Computer Vision (2022): 36-51
2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS) (2022)
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139 (2021): 11953-11963
引用13浏览0EI引用
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作者统计
#Papers: 8
#Citation: 17
H-Index: 2
G-Index: 4
Sociability: 2
Diversity: 0
Activity: 0
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