| Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing B Boecking, N Usuyama, S Bannur, DC Castro, A Schwaighofer, S Hyland, ... European Conference on Computer Vision (ECCV), 2022 | 482 | 2022 |
| Learning to exploit temporal structure for biomedical vision-language processing S Bannur, S Hyland, Q Liu, F Perez-Garcia, M Ilse, DC Castro, B Boecking, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 289 | 2023 |
| Leveraging publicly available data to discern patterns of human-trafficking activity A Dubrawski, K Miller, M Barnes, B Boecking, E Kennedy Journal of Human Trafficking 1 (1), 65-85, 2015 | 124 | 2015 |
| Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling B Boecking, W Neiswanger, EP Xing, A Dubrawski International Conference on Learning Representations (ICLR), 2021 | 108 | 2021 |
| End-to-End Weak Supervision S Rühling Cachay, B Boecking, A Dubrawski Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021 | 71 | 2021 |
| An entity resolution approach to isolate instances of human trafficking online C Nagpal, K Miller, B Boecking, A Dubrawski Proceedings of the 3rd Workshop on Noisy User-generated Text at the ACL …, 2017 | 54 | 2017 |
| Event prediction with learning algorithms—A study of events surrounding the egyptian revolution of 2011 on the basis of micro blog data B Boecking, M Hall, J Schneider Policy & Internet 7 (2), 159-184, 2015 | 47* | 2015 |
| Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection K Hundman, T Gowda, M Kejriwal, B Boecking AAAI/ACM Conference on AI, Ethics, and Society 2018, 2018 | 37 | 2018 |
| Quantifying the relationship between large public events and escort advertising behavior B Boecking, K Miller, E Kennedy, A Dubrawski Journal of human trafficking 5 (3), 220-237, 2019 | 28 | 2019 |
| Weak supervision for affordable modeling of electrocardiogram data M Goswami, B Boecking, A Dubrawski AMIA Annual Symposium Proceedings 2021, 536, 2022 | 18 | 2022 |
| Support vector clustering of time series data with alignment kernels B Boecking, SK Chalup, D Seese, ASW Wong Pattern Recognition Letters 45, 129-135, 2014 | 14 | 2014 |
| MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing B Boecking, N Usuyama, S Bannur, DC de Castro, A Schwaighofer, ... PhysioNet, 2022 | 10 | 2022 |
| Dependency Structure Misspecification in Multi-Source Weak Supervision Models S Rühling Cachay, B Boecking, A Dubrawski ICLR Workshop on Weakly Supervised Learning (WeaSuL), arXiv: 2106.10302, 2021 | 10* | 2021 |
| Killings of social leaders in the Colombian post-conflict: Data analysis for investigative journalism M De-Arteaga, B Boecking arXiv preprint arXiv:1906.08206, 2019 | 7 | 2019 |
| Pairwise Feedback for Data Programming B Boecking, A Dubrawski NeurIPS Workshop on Learning with Rich Experience (LIRE)., 2019 | 6 | 2019 |
| MSCXR-T: Learning to exploit temporal structure for biomedical vision-language processing S Bannur, S Hyland, Q Liu, F Pérez-García, M Ilse, DC de Castro, ... PhysioNet, 2023 | 5 | 2023 |
| Generative Modeling Helps Weak Supervision (and Vice Versa) B Boecking, W Neiswanger, N Roberts, S Ermon, F Sala, A Dubrawski International Conference on Learning Representations (ICLR), 2023 | 5 | 2023 |
| Constrained Clustering and Multiple Kernel Learning without Pairwise Constraint Relaxation B Boecking, V Jeanselme, A Dubrawski Advances in Data Analysis and Classification, 2022 | 4 | 2022 |
| Learning with Diverse Forms of Imperfect and Indirect Supervision B Boecking Carnegie Mellon University, 2023 | 1 | 2023 |
| Predicting Events Surrounding the Egyptian Revolution of 2011 Using Learning Algorithms on Micro Blog Data B Boecking, MA Hall, J Schneider Internet, Politics, and Policy 2014: Crowdsourcing for Politics and Policy …, 2014 | 1 | 2014 |
Artur DubrawskiCarnegie Mellon UniversityVerified email at cs.cmu.edu
