Author:
Wang Jing,Wang Jiang,Ding Jianli
Publisher
Springer Nature Singapore
Reference14 articles.
1. Bhanja, S., Das, A.: Deep neural network for multivariate time-series forecasting. In: Bhattacharjee, D., Kole, D.K., Dey, N., Basu, S., Plewczynski, D. (eds.) Proceedings of International Conference on Frontiers in Computing and Systems. Advances in Intelligent Systems and Computing, vol. 1255, pp. 267–277. Springer, Singapore (2021)
2. Yang, M., Nachum, O.: Representation matters: offline pretraining for sequential decision making. In: Meila, M., Zhang, T. (eds.) Proceedings of the 38th International Conference on Machine Learning, PMLR, vol. 139, pp. 11784–11794. PMLR, New York (2021)
3. Lu, J., Liu, A., Dong, F., et al.: Learning under concept drift: a review. IEEE Trans. Knowl. Data Eng. 31(12), 2346–2363 (2018)
4. Álvarez, V., Mazuelas, S., Lozano, J.A.: Probabilistic load forecasting based on adaptive online learning. IEEE Trans. Power Syst. 36(4), 3668–3680 (2021)
5. Zerveas, G, Jayaraman, S, Patel, D, et al.: A transformer-based framework for multivariate time series representation learning. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 2114–2124. ACM, New York (2021)