| Multiplicative Filter Networks R Fathony, AK Sahu, D Willmott, JZ Kolter International Conference on Learning Representations, 2021 | 154 | 2021 |
| Fairness for robust log loss classification A Rezaei, R Fathony, O Memarrast, B Ziebart Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5511-5518, 2020 | 75 | 2020 |
| Adversarial multiclass classification: A risk minimization perspective R Fathony, A Liu, K Asif, B Ziebart Advances in Neural Information Processing Systems 29, 2016 | 43 | 2016 |
| Adversarial surrogate losses for ordinal regression R Fathony, MA Bashiri, B Ziebart Advances in Neural Information Processing Systems 30, 2017 | 31 | 2017 |
| Distributionally robust graphical models R Fathony, A Rezaei, MA Bashiri, X Zhang, BD Ziebart Advances in Neural Information Processing Systems, 2018 | 26 | 2018 |
| Efficient and consistent adversarial bipartite matching R Fathony, S Behpour, X Zhang, B Ziebart International Conference on Machine Learning, 1457-1466, 2018 | 19 | 2018 |
| Ap-perf: Incorporating generic performance metrics in differentiable learning R Fathony, Z Kolter International Conference on Artificial Intelligence and Statistics, 4130-4140, 2020 | 11 | 2020 |
| Consistent robust adversarial prediction for general multiclass classification R Fathony, K Asif, A Liu, MA Bashiri, W Xing, S Behpour, X Zhang, ... arXiv preprint arXiv:1812.07526, 2018 | 11 | 2018 |
| Partitioning message passing for graph fraud detection W Zhuo, Z Liu, B Hooi, B He, G Tan, R Fathony, J Chen The Twelfth International Conference on Learning Representations, 2024 | 10 | 2024 |
| Fairness for robust learning to rank O Memarrast, A Rezaei, R Fathony, B Ziebart Pacific-Asia Conference on Knowledge Discovery and Data Mining, 544-556, 2023 | 10 | 2023 |
| Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision N Chen, Z Liu, B Hooi, B He, R Fathony, J Hu, J Chen The Twelfth International Conference on Learning Representations, 2024 | 8 | 2024 |
| Fair logistic regression: An adversarial perspective A Rezaei, R Fathony, O Memarrast, BD Ziebart | 8 | 2019 |
| Interaction-focused anomaly detection on bipartite node-and-edge-attributed graphs R Fathony, J Ng, J Chen 2023 International Joint Conference on Neural Networks (IJCNN), 1-10, 2023 | 6 | 2023 |
| Kernel robust bias-aware prediction under covariate shift A Liu, R Fathony, BD Ziebart arXiv preprint arXiv:1712.10050, 2017 | 4 | 2017 |
| Discrete Wasserstein Generative Adversarial Networks (DWGAN) R Fathony, N Goela | 3 | 2018 |
| Fairness for Robust Learning to Rank. CoRR abs/2112.06288 (2021) O Memarrast, A Rezaei, R Fathony, BD Ziebart arXiv preprint arXiv:2112.06288, 2021 | 2 | 2021 |
| Performance-Aligned Learning Algorithms with Statistical Guarantees RZA Fathony University of Illinois at Chicago, 2019 | 1 | 2019 |
| Statistika dan Machine Learning: Satu Ilmu Dua Wajah RZA Fathony Chicago: University of Illinois Chicago, 2015 | 1 | 2015 |
| Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs R Fathony, J Ng, J Chen 2024 International Joint Conference on Neural Networks (IJCNN), 1-10, 2024 | | 2024 |
| Predicting sound pleasantness using regression prediction machine learning model F Schorn, F Lang, T Alber, M Kuka, C Au, FJC CONDESSA, RZA Fathony US Patent App. 17/977,574, 2024 | | 2024 |
Brian D ZiebartProfessor of Computer Science, University of Illinois at ChicagoVerified email at uic.edu
