| Machine unlearning for random forests J Brophy, D Lowd International Conference on Machine Learning, 1092-1104, 2021 | 165 | 2021 |
| Adapting and evaluating influence-estimation methods for gradient-boosted decision trees J Brophy, Z Hammoudeh, D Lowd Journal of Machine Learning Research 24 (154), 1-48, 2023 | 24 | 2023 |
| Instance-based uncertainty estimation for gradient-boosted regression trees J Brophy, D Lowd Advances in Neural Information Processing Systems 35, 11145-11159, 2022 | 17 | 2022 |
| Exit Through the Training Data: A Look into Instance-Attribution Explanations and Efficient Data Deletion in Machine Learning J Brophy University of Oregon, 0 | 9* | |
| Identifying adversarial attacks on text classifiers Z Xie, J Brophy, A Noack, W You, K Asthana, C Perkins, S Reis, S Singh, ... arXiv preprint arXiv:2201.08555, 2022 | 7 | 2022 |
| TREX: Tree-Ensemble Representer-Point Explanations J Brophy, D Lowd ICML'20 Workshop on Extending Explainable AI Beyond Deep Models and …, 2020 | 7 | 2020 |
| Wencong You, Kalyani Asthana, Carter Perkins, Sabrina Reis, Sameer Singh, and Daniel Lowd. 2022 Z Xie, J Brophy, A Noack Identifying adversarial attacks on text classifiers, 0 | 7 | |
| Dart: Data addition and removal trees J Brophy, D Lowd AAAI'21 Workshop on Privacy Preserving AI (PPAI), 2021 | 5 | 2021 |
| Eggs: A flexible approach to relational modeling of social network spam J Brophy, D Lowd AAAI'20 Workshop on Statistical Relational AI (STARAI), 2020 | 4 | 2020 |
| TCAB: A Large-Scale Text Classification Attack Benchmark K Asthana, Z Xie, W You, A Noack, J Brophy, S Singh, D Lowd arXiv preprint arXiv:2210.12233, 2022 | 1 | 2022 |
| Collective classification of social network spam J Brophy, D Lowd Workshops at the Thirty-First AAAI Conference on Artificial Intelligence, 2017 | 1 | 2017 |
| School Shootings in the United States J Brophy Retrieved on July 22, 2018, 2016 | 1 | 2016 |
| The Visual Representation of Sound for the Hearing Impaired J Brophy Cal Poly SLO, 2013 | 1 | 2013 |
| Understanding and Adapting Tree Ensembles: A Training Data Perspective J Brophy University of Oregon, 2022 | | 2022 |
| What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations Z Xie, J Brophy, A Noack, W You, K Asthana, C Perkins, S Reis, ... EMNLP'21 Workshop on Analyzing and Interpreting Neural Networks for NLP …, 2021 | | 2021 |
Daniel LowdAssociate Professor of Computer Science, University of OregonПотвърден имейл адрес: cs.uoregon.edu
