Robustness guarantees for deep neural networks on videos

被引：0
|
作者：
Wu, Min [1 ]
Kwiatkowska, Marta [1 ]
机构：
[1] Department of Computer Science, University of Oxford, United Kingdom
来源：
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition | 2020年
基金：
欧盟地平线“2020”;
关键词：
Gradient-based search - Learning models - Lipschitz continuity - Minimum distance - Optimisation problems - Spatial features - Temporal dynamics - Upper and lower bounds;
D O I：
9157167
中图分类号：
学科分类号：
摘要：
32
引用
收藏
页码：308 / 317
相关论文
共 50 条
  • [1] Robustness Guarantees for Deep Neural Networks on Videos
    Wu, Min
    Kwiatkowska, Marta
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 308 - 317
  • [2] Adversarial Robustness Guarantees for Random Deep Neural Networks
    De Palma, Giacomo
    Kiani, Bobak T.
    Lloyd, Seth
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139, 2021, 139
  • [3] Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance
    Ruan, Wenjie
    Wu, Min
    Sun, Youcheng
    Huang, Xiaowei
    Kroening, Daniel
    Kwiatkowska, Marta
    PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2019, : 5944 - 5952
  • [4] Statistical Guarantees for the Robustness of Bayesian Neural Networks
    Cardelli, Luca
    Kwiatkowska, Marta
    Laurenti, Luca
    Paoletti, Nicola
    Patane, Andrea
    Wicker, Matthew
    PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2019, : 5693 - 5700
  • [5] Robustness Guarantees for Adversarially Trained Neural Networks
    Mianjy, Poorya
    Arora, Raman
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023), 2023,
  • [6] ε-Weakened Robustness of Deep Neural Networks
    Huang, Pei
    Yang, Yuting
    Liu, Minghao
    Jia, Fuqi
    Ma, Feifei
    Zhang, Jian
    PROCEEDINGS OF THE 31ST ACM SIGSOFT INTERNATIONAL SYMPOSIUM ON SOFTWARE TESTING AND ANALYSIS, ISSTA 2022, 2022, : 126 - 138
  • [7] Analytical Guarantees on Numerical Precision of Deep Neural Networks
    Sakr, Charbel
    Kim, Yongjune
    Shanbhag, Naresh
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 70, 2017, 70
  • [8] Reachability Analysis of Deep Neural Networks with Provable Guarantees
    Ruan, Wenjie
    Huang, Xiaowei
    Kwiatkowska, Marta
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 2651 - 2659
  • [9] Robustness Verification Boosting for Deep Neural Networks
    Feng, Chendong
    2019 6TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2019), 2019, : 531 - 535
  • [10] Analyzing the Noise Robustness of Deep Neural Networks
    Liu, Mengchen
    Liu, Shixia
    Su, Hang
    Cao, Kelei
    Zhu, Jun
    2018 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), 2018, : 60 - 71
12345