Rizal Fathony
Rizal Fathony
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Adversarial surrogate losses for ordinal regression
R Fathony, MA Bashiri, B Ziebart
Advances in Neural Information Processing Systems, 563-573, 2017
122017
Adversarial multiclass classification: A risk minimization perspective
R Fathony, A Liu, K Asif, B Ziebart
Advances in Neural Information Processing Systems, 559-567, 2016
122016
Efficient and consistent adversarial bipartite matching
R Fathony, S Behpour, X Zhang, B Ziebart
International Conference on Machine Learning, 1457-1466, 2018
72018
Distributionally robust graphical models
R Fathony, A Rezaei, MA Bashiri, X Zhang, B Ziebart
Advances in Neural Information Processing Systems, 8344-8355, 2018
72018
Fair logistic regression: An adversarial perspective
A Rezaei, R Fathony, O Memarrast, B Ziebart
arXiv preprint arXiv:1903.03910, 2019
42019
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
22018
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning
R Fathony, JZ Kolter
arXiv preprint arXiv:1912.00965, 2019
12019
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
Fairness for Robust Log Loss Classification
A Rezaei, R Fathony, O Memarrast, B Ziebart
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