Kaixuan Chen

2023

Automated labeling and online evaluation for self-paced movement detection BCI

Zhang, D., Hansen, C., De Frène, F., Kærgaard, S. P., Qian, W. & Chen, K., 8 Apr 2023, In: Knowledge-Based Systems. 265, 110383.

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

Open Access

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2 Citations (Scopus)

15 Downloads (Pure)

Probabilistic Forecasts of Global Horizontal Irradiance for Solar Systems

Jonler, J. F., Bruno Lottrup, F., Berg, B., Zhang, D. & Chen, K., 1 Jan 2023, In: IEEE Sensors Letters. 7, 1, p. 1-4 4 p., 7000104.

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

4 Citations (Scopus)

Worker-Churn-based Task Assignment with Context-LSTM in Spatial Crowdsourcing

Zhao, Y., Lai, T., Wang, Z., Chen, K., Li, H. & Zheng, K., 1 Sept 2023, In: I E E E Transactions on Knowledge & Data Engineering. 35, 9, p. 9783-9796 14 p., 10054427.

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

2 Citations (Scopus)

2022

Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey.

Zhang, D., Chen, K., Zhao, Y., Yang, B., Yao, L. & Jensen, C. S., 2022, arXiv.

Research output: Working paper/Preprint › Preprint

Open Access

Preventing Sensitive Information Leakage from Mobile Sensor Signals via IntegrativeTransformation

Zhang, D., Yao, L., Chen, K., Yang, Z., Gao, X. & Liu, Y., 1 Dec 2022, In: IEEE Transactions on Mobile Computing. 21, 12, p. 4517-4528 12 p., 9424974.

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

Open Access

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3 Citations (Scopus)

95 Downloads (Pure)

2021

Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities

Chen, K., Zhang, D., Yao, L., Guo, B., Yu, Z. & Liu, Y., Jul 2021, In: ACM Computing Surveys. 54, 4, p. 1-40 40 p., 77.

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

356 Citations (Scopus)

HeatFlex: Machine learning based data-driven flexibility prediction for individual heat pumps

Brusokas, J., Pedersen, T. B., Siksnys, L., Zhang, D. & Chen, K., 22 Jun 2021, e-Energy '21: Proceedings of the Twelfth ACM International Conference on Future Energy Systems. New York: Association for Computing Machinery, p. 160-170 11 p.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Open Access

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6 Citations (Scopus)

160 Downloads (Pure)

2020

A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition

Chen, K., Yao, L., Zhang, D., Wang, X., Chang, X. & Nie, F., May 2020, In: IEEE Transactions on Neural Networks and Learning Systems. 31, 5, p. 1747-1756 10 p., 8767027.

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

276 Citations (Scopus)

Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition

Zhang, D., Yao, L., Chen, K., Wang, S., Chang, X. & Liu, Y., Jul 2020, In: IEEE Transactions on Cybernetics. 50, 7, p. 3033-3044 12 p., 8698218.

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

248 Citations (Scopus)

Motor Imagery Classification via Temporal Attention Cues of Graph Embedded EEG Signals

Zhang, D., Chen, K., Jian, D. & Yao, L., Sept 2020, In: IEEE Journal of Biomedical and Health Informatics. 24, 9, p. 2570-2579 10 p., 8961150.

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

89 Citations (Scopus)

2019

A Convolutional Recurrent Attention Model for Subject-Independent EEG Signal Analysis

Zhang, D., Yao, L., Chen, K. & Monaghan, J., May 2019, In: IEEE Signal Processing Letters. 26, 5, p. 715-719 5 p., 8675451.

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

135 Citations (Scopus)

A Convolutional Recurrent Attention Model for Subject-Independent EEG Signal Analysis

Zhang, D., Yao, L., Chen, K. & Monaghan, J., May 2019, In: IEEE Signal Processing Letters. 26, 5, p. 715-719 5 p., 8675451.

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

135 Citations (Scopus)

A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals

Zhang, D., Yao, L., Chen, K., Wang, S., Haghighi, P. D. & Sullivan, C., Nov 2019, In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27, 11, p. 2247-2253 7 p., 8847648.

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

45 Citations (Scopus)

A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals

Zhang, D., Yao, L., Chen, K., Wang, S., Haghighi, P. D. & Sullivan, C., Nov 2019, In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27, 11, p. 2247-2253 7 p., 8847648.

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

46 Citations (Scopus)

Collective protection: Preventing sensitive inferences via integrative transformation

Zhang, D., Yao, L., Chen, K., Long, G. & Wang, S., Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). IEEE, p. 1498-1503 6 p. 8970834. (Proceedings - IEEE International Conference on Data Mining, ICDM, Vol. 2019-November).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

10 Citations (Scopus)

Distributionally robust semi-supervised learning for people-centric sensing

Chen, K., Yao, L., Zhang, D., Chang, X., Long, G. & Wang, S., 2019, 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI Press, p. 3321-3328 8 p. (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

29 Citations (Scopus)

Learning attentional temporal cues of brainwaves with spatial embedding for motion intent detection

Zhang, D., Chen, K., Jian, D., Yao, L., Wang, S. & Li, P., Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). IEEE, p. 1450-1455 6 p. 8970671. (Proceedings - IEEE International Conference on Data Mining, ICDM, Vol. 2019-November).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

9 Citations (Scopus)

Multi-agent attentional activity recognition

Chen, K., Yao, L., Zhang, D., Guo, B. & Yu, Z., 2019, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Kraus, S. (ed.). International Joint Conferences on Artificial Intelligence, p. 1344-1350 7 p. (IJCAI International Joint Conference on Artificial Intelligence, Vol. 2019-August).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Open Access

21 Citations (Scopus)

Multi-agent attentional activity recognition

Chen, K., Yao, L., Zhang, D., Guo, B. & Yu, Z., 2019, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Kraus, S. (ed.). International Joint Conferences on Artificial Intelligence, p. 1344-1350 7 p. (IJCAI International Joint Conference on Artificial Intelligence, Vol. 2019-August).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Open Access

21 Citations (Scopus)

2018

Fuzzy integral optimization with deep Q-network for EEG-based intention recognition

Zhang, D., Yao, L., Wang, S., Chen, K., Yang, Z. & Benatallah, B., 2018, Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings. Phung, D., Webb, G. I., Ho, B., Tseng, V. S., Ganji, M. & Rashidi, L. (eds.). Physica-Verlag, p. 156-168 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10937 LNAI).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

13 Citations (Scopus)

Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling

Chen, K., Yao, L., Wang, X., Zhang, D., Gu, T., Yu, Z. & Yang, Z., 10 Oct 2018, 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings. IEEE, 8489767. (Proceedings of the International Joint Conference on Neural Networks, Vol. 2018-July).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

28 Citations (Scopus)

Ready for use: Subject-independent movement intention recognition via a convolutional attention model

Zhang, D., Chen, K., Yao, L. & Wang, S., 17 Oct 2018, CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Paton, N., Candan, S., Wang, H., Allan, J., Agrawal, R., Labrinidis, A., Cuzzocrea, A., Zaki, M., Srivastava, D., Broder, A. & Schuster, A. (eds.). Association for Computing Machinery, p. 1763-1766 4 p. (International Conference on Information and Knowledge Management, Proceedings).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

19 Citations (Scopus)

Kaixuan Chen

Research output

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