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Jie Lin
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Improving the Transferability of Adversarial Examples via Direction Tuning


Mar 27, 2023
Xiangyuan Yang, Jie Lin, Hanlin Zhang, Xinyu Yang, Peng Zhao

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Fuzziness-tuned: Improving the Transferability of Adversarial Examples


Mar 17, 2023
Xiangyuan Yang, Jie Lin, Hanlin Zhang, Xinyu Yang, Peng Zhao

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Hybrid Multimodal Feature Extraction, Mining and Fusion for Sentiment Analysis


Aug 12, 2022
Jia Li, Ziyang Zhang, Junjie Lang, Yueqi Jiang, Liuwei An, Peng Zou, Yangyang Xu, Sheng Gao, Jie Lin, Chunxiao Fan, Xiao Sun, Meng Wang

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* 8 pages, 2 figures, to appear in MuSe 2022 (ACM MM2022 co-located workshop) 
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Long-tailed Recognition by Learning from Latent Categories


Jun 02, 2022
Weide Liu, Zhonghua Wu, Yiming Wang, Henghui Ding, Fayao Liu, Jie Lin, Guosheng Lin

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FACM: Correct the Output of Deep Neural Network with Middle Layers Features against Adversarial Samples


Jun 02, 2022
Xiangyuan Yang, Jie Lin, Hanlin Zhang, Xinyu Yang, Peng Zhao

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Mask-Guided Divergence Loss Improves the Generalization and Robustness of Deep Neural Network


Jun 02, 2022
Xiangyuan Yang, Jie Lin, Hanlin Zhang, Xinyu Yang, Peng Zhao

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OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization


May 23, 2022
Peng Hu, Xi Peng, Hongyuan Zhu, Mohamed M. Sabry Aly, Jie Lin

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* Accepted in AAAI2021 and Just upload to retrieve Arxiv DOI for Project Record 
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Enhancing the Transferability of Adversarial Examples via a Few Queries


May 19, 2022
Xiangyuan Yang, Jie Lin, Hanlin Zhang, Xinyu Yang, Peng Zhao

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On Representation Knowledge Distillation for Graph Neural Networks


Nov 09, 2021
Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan-Sheng Foo

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