David Jonathan Miller

    • 1836 Citations
    • 25 h-Index
    1992 …2020

    Research output per year

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    Research Output

    Adversarial Learning Targeting Deep Neural Network Classification: A Comprehensive Review of Defenses against Attacks

    Miller, D. J., Xiang, Z. & Kesidis, G., Mar 2020, In : Proceedings of the IEEE. 108, 3, p. 402-433 32 p., 9013065.

    Research output: Contribution to journalArticle

  • Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation

    Zhong, H., Liao, C., Squicciarini, A. C., Zhu, S. & Miller, D., Mar 16 2020, CODASPY 2020 - Proceedings of the 10th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc, p. 97-108 12 p. (CODASPY 2020 - Proceedings of the 10th ACM Conference on Data and Application Security and Privacy).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Improved parsimonious topic modeling based on the bayesian information criterion

    Wang, H. & Miller, D., Mar 1 2020, In : Entropy. 22, 3, 326.

    Research output: Contribution to journalArticle

    Open Access
  • Scanning the Issue

    Liu, W., John, M., Karrenbauer, A., Allerhand, A., Lombardi, F., Shulte, M., Miller, D. J., Xiang, Z., Kesidis, G., Oulasvirta, A., Dayama, N. R. & Shiripour, M., Mar 2020, In : Proceedings of the IEEE. 108, 3, p. 400-401 2 p., 9024191.

    Research output: Contribution to journalReview article

  • A Benchmark Study of Backdoor Data Poisoning Defenses for Deep Neural Network Classifiers and A Novel Defense

    Xiang, Z., Miller, D. J. & Kesidis, G., Oct 2019, 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing, MLSP 2019. IEEE Computer Society, 8918908. (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; vol. 2019-October).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 1 Scopus citations