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  1. 2024

  2. Explainable AI: Efficiency Sequential Shapley Updating Approach

    Петросян, О. Л. & Цзоу, Ц., 2024, In: IEEE Access. 12, p. 166414-166423

    Research output: Contribution to journal › Article › peer-review

  3. 2023

  4. Explainable AI: Graph Based Sampling Approach for High Dimensional AI System

    Zou, J., Xu, F., Petrosian, O. & Li, Y., 21 Sep 2023, In: Lecture Notes in Networks and Systems. 776, p. 410-422 13 p.

    Research output: Contribution to journal › Article › peer-review

  5. 2021

  6. High-Dimensional Explainable AI for Cancer Detection

    Zou, J., Xu, F., Zhang, Y., Petrosian, O. & Krinkin, K., 1 Sep 2021, In: International Journal of Artificial Intelligence. 19, 2, p. 195-217 23 p.

    Research output: Contribution to journal › Article › peer-review

  7. Evolutionary algorithms in high-dimensional radio access network optimization

    Semenchikov, D., Filippova, A., Volf, D., Kovrizhnykh, N., Mironov, M., Jinying, Z., Ronghui, L., Yuanming, Z., Dapeng, C. & Wei, H., 8 Jul 2021, p. 1834-1841.

    Research output: Contribution to conference › Paper › peer-review

  8. 2020

  9. Explainable AI: Using shapley value to explain complex anomaly detection ML-based systems

    Zou, J. & Petrosian, O., 2 Dec 2020, Machine Learning and Artificial Intelligence : Proceedings of MLIS 2020. Tallon-Ballesteros, A. J. & Chen, C-H. (eds.). IOS Press, p. 152-164 (Frontiers in Artificial Intelligence and Applications; vol. 332).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  10. Explainable AI: Using Shapley Value to Explain the Anomaly Detection System Based on Machine Learning Approaches.

    Zou, J., 2020, In: ПРОЦЕССЫ УПРАВЛЕНИЯ И УСТОЙЧИВОСТЬ. 7, 1, p. 355-360

    Research output: Contribution to journal › Article

ID: 13793587