| Personalized policy learning using longitudinal mobile health data X Hu, M Qian, B Cheng, YK Cheung Journal of the American Statistical Association 116 (533), 410-420, 2021 | 16 | 2021 |
| DeeprETA: an ETA post-processing system at scale X Hu, T Binaykiya, E Frank, O Cirit arXiv preprint arXiv:2206.02127, 2022 | 10 | 2022 |
| A first step towards behavioral coaching for managing stress: a case study on optimal policy estimation with multi-stage threshold Q-learning X Hu, PYS Hsueh, CH Chen, KM Diaz, YKK Cheung, M Qian AMIA Annual Symposium Proceedings 2017, 930, 2017 | 8 | 2017 |
| Deepeta: How uber predicts arrival times using deep learning X Hu, O Cirit, T Binaykiya, R Hora Uber AI 2, 2022 | 7 | 2022 |
| Applying svgd to bayesian neural networks for cyclical time-series prediction and inference X Hu, P Szerlip, T Karaletsos, R Singh NeurIPS 2018 Bayesian Deep Learning workshop, 2019 | 7 | 2019 |
| An interpretable health behavioral intervention policy for mobile device users X Hu, PYS Hsueh, CH Chen, KM Diaz, FE Parsons, I Ensari, M Qian, ... IBM journal of research and development 62 (1), 4: 1-4: 6, 2018 | 7 | 2018 |
| Adaptive adjustment using sensor data and distributed data HY Chang, CH Chen, JV Codella, PY Hsueh, X Hu US Patent 11,228,613, 2022 | 2 | 2022 |
| When does loss-based prioritization fail? NT Hu, X Hu, R Liu, S Hooker, J Yosinski ICML 2021 Subset Selection in Machine Learning: From Theory to Applications, 2021 | 2 | 2021 |
| Smart learning using big and small data for mobile and IOT e-Health PYS Hsueh, X Hu, YK Cheung, D Wolff, M Marschollek, J Rogers Intelligent Internet of Things: From Device to Fog and Cloud, 607-636, 2020 | 1 | 2020 |
| Personalized Policy Learning using Longitudinal Mobile Health Data (Supplementary Material) X Hu, M Qian, B Cheng, YK Cheung | | |
