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  1. 2025

  2. Complete-to-Sparse: A Novel Graph Construction Strategy for Efficient ShapG

    Чжао, Ч., Лю, Ц. & Парилина, Е. М., 6 Jul 2025, Mathematical Optimization Theory and Operations Research (MOTOR 2025). Springer Nature, p. 180-194 15 p. ( Lecture Notes in Computer Science; vol. 15681).

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

  3. ShapG: new feature importance method based on the Shapley value

    Чжао, Ч., Лю, Ц. & Парилина, Е. М., 15 May 2025, In: Engineering Applications of Artificial Intelligence. 148, 110409.

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

  4. 2023

  5. Long-Term Forecasting of Air Pollution Particulate Matter (PM2. 5) and Analysis of Influencing Factors

    Zhang, Y., Sun, Q., Liu, J. & Petrosian, O., 19 Dec 2023, In: Sustainability. 16, 1, 19.

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

  6. ShapTime: A General XAI Approach for Explainable Time Series Forecasting

    Zhang, Y., Sun, Q., Qi, D., Liu, J., Ma, R. & Petrosian, O., 2023, (Accepted/In press) In: Lecture Notes in Networks and Systems. 15 p.

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

  7. 2022

  8. Prediction of Next App in OS

    Ma, R., Zhang, Y., Liu, J., Petrosian, O. & Krinkin, K., 16 Jun 2022, Proceedings of 2022 3rd International Conference on Neural Networks and Neurotechnologies, NeuroNT 2022. Shaposhnikov, S. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 28-31 4 p. (Proceedings of 2022 3rd International Conference on Neural Networks and Neurotechnologies, NeuroNT 2022).

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

  9. FI-SHAP: Explanation of Time Series Forecasting and Improvement of Feature Engineering Based on Boosting Algorithm

    Zhang, Y., Petrosian, O., Liu, J., Ma, R. & Krinkin, K. V., 2022, Intelligent Systems and Applications: Proceedings of the 2022 Intelligent Systems Conference (IntelliSys). Springer Nature, Vol. 3. p. 745–758 (Lecture Notes in Networks and Systems; no. 544).

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

  10. Forecasting and XAI for Applications Usage in OS

    Ma, R., Zhang, Y., Liu, J., Li, Y., Petrosian, O. & Krinkin, K. V., 2022, Machine Learning and Artificial Intelligence. IOS Press, p. 17-27 (Frontiers in Artificial Intelligence and Applications; no. 360).

    Research output: Chapter in Book/Report/Conference proceeding › Article in an anthology › Research › peer-review

  11. NEXT RUNNING APPLICATION PREDICTION IN OS USING TIME-SERIES FORECASTING AND XAI

    Ma, R., Zhang, Y., Liu, J. & Petrosian, O., 2022, In: ПРОЦЕССЫ УПРАВЛЕНИЯ И УСТОЙЧИВОСТЬ. 9, 1, p. 329-338

    Research output: Contribution to journal › Conference article › peer-review

  12. 2021

  13. Comparison and explanation of forecasting algorithms for energy time series

    Zhang, Y., Ma, R., Liu, J., Liu, X., Petrosian, O. & Krinkin, K., 1 Nov 2021, In: Mathematics. 9, 21, 2794.

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

ID: 45953847