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Results: 5
Number of items: 5
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Wang, S., Scheider, S., Sporrel, K., Deutekom, M., Timmer, J., & Kröse, B. (2021). What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data. Frontiers in Public Health, 8, Article 536370. https://doi.org/10.3389/fpubh.2020.536370 -
Wang, S., Sporrel, K., van Hoof, H., Simons, M., de Boer, R. D. D., Ettema, D., Nibbeling, N., Deutekom, M., & Kröse, B. (2021). Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study. International Journal of Environmental Research and Public Health, 18(11), Article 6059. https://doi.org/10.3390/ijerph18116059
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Wang, S., Zhang, C., Kröse, B., & van Hoof, H. (2021). Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator. Journal of medical systems, 45(12), Article 102. https://doi.org/10.1007/s10916-021-01773-0
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Qi, J., Bloemen, V., Wang, S., van Wijk, J., & van de Wetering, H. (2020). STBins: Visual Tracking and Comparison of Multiple Data Sequences Using Temporal Binning. IEEE Transactions on visualization and computer graphics, 26(1), 1054-1063. https://doi.org/10.1109/TVCG.2019.2934289
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Wang, S., Timmer, J. A., Scheider, S., Sporrel, K., Akata, Z., & Kröse, B. (2018). A Data-driven Study on Preferred Situations for Running. In UbiComp/ISWC '18 adjunct: proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and proceedings of the 2018 ACM International Symposium on Wearable Computers : October 8-12, 2018, Singapore, Singapore (pp. 283-286). The Association for Computing Machinery. https://doi.org/10.1145/3267305.3267552
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