| Time-Aware Transformer-based Network for Clinical Notes Series Prediction D Zhang, J Thadajarassiri, C Sen, E Rundensteiner Proceedings of Machine Learning Research 126, 566-588, 2020 | 36 | 2020 |
| Crowdsourcing and Machine Learning Approaches for Extracting Entities Indicating Potential Foodborne Outbreaks From Social Media D Tao, D Zhang, R Hu, E Rundensteiner, H Feng Scientific Reports, 2021 | 10 | 2021 |
| TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks R Hu, D Zhang, D Tao, T Hartvigsen, H Feng, E Rundensteiner Proceedings of the Thirteenth Language Resources and Evaluation Conference …, 2022 | 4 | 2022 |
| Human-like Explanation for Text Classification With Limited Attention Supervision D Zhang, C Sen, J Thadajarassiri, T Hartvigsen, X Kong, E Rundensteiner 2021 IEEE International Conference on Big Data (Big Data), 2021 | 3 | 2021 |
| Uce-fid: Using large unlabeled, medium crowdsourced-labeled, and small expert-labeled tweets for foodborne illness detection R Hu, D Zhang, D Tao, H Zhang, H Feng, E Rundensteiner 2023 IEEE International Conference on Big Data (BigData), 5250-5259, 2023 | 2 | 2023 |
| A novel foodborne illness detection and web application tool based on social media D Tao, R Hu, D Zhang, J Laber, A Lapsley, T Kwan, L Rathke, ... Foods 12 (14), 2769, 2023 | 2 | 2023 |
| Epidemiological data mining for assisting with foodborne outbreak investigation D Tao, D Zhang, R Hu, E Rundensteiner, H Feng Foods 12 (20), 3825, 2023 | 1 | 2023 |
| FATA-Trans: Field and Time-Aware Transformer for Sequential Tabular Data D Zhang, L Wang, X Dai, S Jain, J Wang, Y Fan, MCC Yeh, Y Zheng, ... Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 1 | 2023 |
| 众筹在林业领域的应用前景探讨 刘川源， 尹煊媛， 张东宇 现代商贸工业 36 (9), 104-108, 2015 | 1 | 2015 |
| CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance D Zhang, R Hu, E Rundensteiner Proceedings of the 2024 SIAM International Conference on Data Mining (SDM), 2024 | | 2024 |
| (v) Crowdsourcing and Machine Learning Approaches for Extracting Information Indicating Potential Foodborne Outbreak from Social Media D Tao, D Zhang, R Hu, E Rundensteiner, H Feng IAFP 2021, 2021 | | 2021 |
| 国有林场购买社会服务的意愿及其影响因素的实证分析 张慧， 施慧仪， 李益禛， 张东宇 消费导刊, 45-47, 2016 | | 2016 |
| Crowd-MIA: A Crowdsourced Dataset for Multi-grained Weakly Supervised Learning R Hu, D Zhang, D Tao, T Hartvigsen, H Feng, E Rundensteiner | | |
| TWEET-FD: A Dataset for Multiple Foodborne Illness Incident Detection Tasks R Hu, D Zhang, D Tao, H Feng, E Rundensteiner City 7, 31, 0 | | |
Elke RundensteinerThe William Smith Dean's Professor, Computer Science; Founding Head, Data Science Program; WorcesterVerified email at wpi.edu
