| Adaptive laplace mechanism: Differential privacy preservation in deep learning NH Phan, X Wu, H Hu, D Dou 2017 IEEE international conference on data mining (ICDM), 385-394, 2017 | 221 | 2017 |
| Scalable differential privacy with certified robustness in adversarial learning H Phan, MT Thai, H Hu, R Jin, T Sun, D Dou International Conference on Machine Learning, 7683-7694, 2020 | 55 | 2020 |
| An ensemble deep learning model for drug abuse detection in sparse twitter-sphere H Hu, NH Phan, J Geller, S Iezzi, H Vo, D Dou, S Chun MEDINFO 2019: Health and Wellbeing e-Networks for All, 163-167, 2019 | 29 | 2019 |
| An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning H Hu, NH Phan, SA Chun, J Geller, H Vo, X Ye, R Jin, K Ding, D Kenne, ... Computational Social Networks 6, 1-19, 2019 | 28 | 2019 |
| Deep self-taught learning for detecting drug abuse risk behavior in tweets H Hu, NH Phan, J Geller, H Vo, B Manasi, X Huang, S Di Lorio, T Dinh, ... Computational Data and Social Networks: 7th International Conference, CSoNet …, 2018 | 22 | 2018 |
| Deep learning model for classifying drug abuse risk behavior in tweets H Hu, P Moturu, K Dharan, J Geller, S Iorio, H Phan, H Vo, S Chun 2018 IEEE International conference on healthcare informatics (ICHI), 386-387, 2018 | 18 | 2018 |
| Ontology-based interpretable machine learning for textual data P Lai, NH Phan, H Hu, A Badeti, D Newman, D Dou 2020 International Joint Conference on Neural Networks (IJCNN), 1-10, 2020 | 15 | 2020 |
| Preserving differential privacy in adversarial learning with provable robustness NH Phan, R Jin, MT Thai, H Hu, D Dou arXiv preprint arXiv:1903.09822, 2019 | 11 | 2019 |
| Flsys: Toward an open ecosystem for federated learning mobile apps X Jiang, H Hu, T On, P Lai, VD Mayyuri, A Chen, DM Shila, A Larmuseau, ... IEEE Transactions on Mobile Computing 23 (1), 501-519, 2022 | 9 | 2022 |
| Drugtracker: A community-focused drug abuse monitoring and supporting system using social media and geospatial data (demo paper) H Hu, NH Phan, X Ye, R Jin, K Ding, D Dou, HT Vo Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances …, 2019 | 8 | 2019 |
| OnML: an ontology-based approach for interpretable machine learning P Ayranci, P Lai, N Phan, H Hu, A Kolinowski, D Newman, D Dou Journal of Combinatorial Optimization 44 (1), 770-793, 2022 | 7 | 2022 |
| User-Entity Differential Privacy in Learning Natural Language Models P Lai, NH Phan, T Sun, R Jain, F Dernoncourt, J Gu, N Barmpalios 2022 IEEE International Conference on Big Data (Big Data), 1465-1474, 2022 | 1 | 2022 |
| Scalable self-taught deep-embedded learning framework for drug abuse spatial behaviors detection W Liu, X Ye, H Phan, H Hu Computational Data and Social Networks: 8th International Conference, CSoNet …, 2019 | 1 | 2019 |
| Recursive Structure Similarity: A Novel Algorithm for Graph Clustering H Hu, Y Fang, R Jin, W Xiong, X Qian, D Dou, H Phan 2018 IEEE 30th International Conference on Tools with Artificial …, 2018 | 1 | 2018 |
| Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning P Lai, H Hu, H Phan, R Jin, M Thai, A Chen Conference on Lifelong Learning Agents, 778-797, 2022 | | 2022 |
| Private and Federated Deep Learning: System, Theory, and Applications for Social Good H Hu New Jersey Institute of Technology, 2021 | | 2021 |
| Differential Privacy in Adversarial Learning with Provable Robustness NH Phan, MT Thai, R Jin, H Hu, D Dou | | |
| Ontology-based Interpretable Machine Learning with Learnable Anchors P Lai, NH Phan, D Newman, H Hu, A Badeti, D Dou | | |
