| Deploying an interactive machine learning system in an evidence-based practice center: abstrackr BC Wallace, K Small, CE Brodley, J Lau, TA Trikalinos Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium …, 2012 | 772 | 2012 |
| Margin-based active learning for structured output spaces D Roth, K Small European Conference on Machine Learning, 413-424, 2006 | 295 | 2006 |
| Class imbalance, redux BC Wallace, K Small, CE Brodley, TA Trikalinos 2011 IEEE 11th International Conference on Data Mining, 754-763, 2011 | 294 | 2011 |
| Active learning for biomedical citation screening BC Wallace, K Small, CE Brodley, TA Trikalinos Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 164 | 2010 |
| Unsupervised rank aggregation with distance-based models A Klementiev, D Roth, K Small Proceedings of the 25th international conference on Machine learning, 472-479, 2008 | 133 | 2008 |
| An unsupervised learning algorithm for rank aggregation A Klementiev, D Roth, K Small European Conference on Machine Learning, 616-623, 2007 | 124 | 2007 |
| Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering L Zhou, K Small arXiv preprint arXiv:1911.06192, 2019 | 109 | 2019 |
| Toward modernizing the systematic review pipeline in genetics: efficient updating via data mining BC Wallace, K Small, CE Brodley, J Lau, CH Schmid, L Bertram, CM Lill, ... Genetics in Medicine 14 (7), 663-669, 2012 | 91 | 2012 |
| Who should label what? Instance allocation in multiple expert active learning BC Wallace, K Small, CE Brodley, TA Trikalinos Proceedings of the SIAM International Conference on Data Mining (SDM), 2011 | 85 | 2011 |
| Unsupervised rank aggregation with domain-specific expertise A Klementiev, D Roth, K Small, I Titov Twenty-First International Joint Conference on Artificial Intelligence, 2009 | 76 | 2009 |
| The constrained weight space svm: learning with ranked features K Small, B Wallace, C Brodley, T Trikalinos the 28th International Conference on Machine Learning (ICML), 2011 | 62 | 2011 |
| Relation alignment for textual entailment recognition M Sammons, VGV Vydiswaran, T Vieira, N Johri, MW Chang, ... Text Analysis Conference (TAC), 2009 | 55 | 2009 |
| The role of semantic information in learning question classifiers X Li, D Roth, K Small Proceedings of the International Joint Conference on Natural Language Processing, 2004 | 55 | 2004 |
| Newsclaims: A new benchmark for claim detection from news with attribute knowledge RG Reddy, SC Chinthakindi, Z Wang, Y Fung, K Conger, A Elsayed, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 53* | 2022 |
| End-to-end offline goal-oriented dialog policy learning via policy gradient L Zhou, K Small, O Rokhlenko, C Elkan arXiv preprint arXiv:1712.02838, 2017 | 51 | 2017 |
| Challenges and Opportunities in Applied Machine Learning CE Brodley, U Rebbapragada, K Small, B Wallace AI Magazine 33 (1), 11-24, 2012 | 51 | 2012 |
| Inverse Reinforcement Learning with Natural Language Goals L Zhou, K Small arXiv preprint arXiv:2008.06924, 2020 | 50 | 2020 |
| Proceedings of the 2nd ACM SIGHIT international health informatics symposium BC Wallace, K Small, CE Brodley, J Lau, TA Trikalinos ACM, 819-824, 2012 | 46 | 2012 |
| Methods for the joint meta‐analysis of multiple tests TA Trikalinos, DC Hoaglin, KM Small, N Terrin, CH Schmid Research Synthesis Methods 5 (4), 294-312, 2014 | 45 | 2014 |
| Margin-based active learning for structured predictions K Small, D Roth International Journal of Machine Learning and Cybernetics 1 (1-4), 3-25, 2010 | 42 | 2010 |
Dan RothProfessor of Computer Science, University of PennsylvaniaVerified email at seas.upenn.edu
