Rizal Fathony
Rizal Fathony
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Adversarial multiclass classification: A risk minimization perspective
R Fathony, A Liu, K Asif, B Ziebart
Advances in Neural Information Processing Systems 29, 559-567, 2016
222016
Adversarial Surrogate Losses for Ordinal Regression.
R Fathony, MA Bashiri, BD Ziebart
NIPS, 563-573, 2017
192017
Efficient and consistent adversarial bipartite matching
R Fathony, S Behpour, X Zhang, B Ziebart
International Conference on Machine Learning, 1457-1466, 2018
132018
Distributionally robust graphical models
R Fathony, A Rezaei, MA Bashiri, X Zhang, BD Ziebart
arXiv preprint arXiv:1811.02728, 2018
122018
Fair logistic regression: An adversarial perspective
A Rezaei, R Fathony, O Memarrast, B Ziebart
arXiv preprint arXiv:1903.03910, 2019
52019
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
52018
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
42020
AP-perf: Incorporating generic performance metrics in differentiable learning
R Fathony, Z Kolter
International Conference on Artificial Intelligence and Statistics, 4130-4140, 2020
32020
Performance-Aligned Learning Algorithms with Statistical Guarantees
RZA Fathony
University of Illinois at Chicago, 2019
2019
Kernel Robust Bias-Aware Prediction under Covariate Shift
A Liu, R Fathony, BD Ziebart
arXiv preprint arXiv:1712.10050, 2017
2017
MULTIPLICATIVE FILTER NETWORKS
R Fathony, AK Sahu, AA AI, D Willmott, JZ Kolter
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