Funder
Guangxi Key Research and Development Program
National Natural Science Foundation of China
National Key Research and Development Program of China
Reference60 articles.
1. Improving sentiment domain adaptation for Arabic using an unsupervised self-labeling framework
2. Anguita, D., Ghio, A., Oneto, L., Parra Perez, X., & Reyes Ortiz, J. L. (2013). A public domain dataset for human activity recognition using smartphones. In Proceedings of the 21th international european symposium on artificial neural networks, computational intelligence and machine learning (pp. 437–442).
3. Cai, R., Chen, J., Li, Z., Chen, W., Zhang, K., Ye, J., et al. (2021). Time series domain adaptation via sparse associative structure alignment. In Proceedings of the AAAI conference on artificial intelligence, vol. 35, no. 8 (pp. 6859–6867).
4. Chen, M.-H., Kira, Z., AlRegib, G., Yoo, J., Chen, R., & Zheng, J. (2019). Temporal attentive alignment for large-scale video domain adaptation. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 6321–6330).
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