2019

  1. Distributionally Robust Graphical Models Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang, and Brian Ziebart Workshop: The 3rd Workshop On Tractable Probabilistic Modeling @ ICML 2019
  2. Performance-Aligned Learning Algorithms with Statistical Guarantees Rizal Fathony PhD Thesis: University of Illinois at Chicago 2019 PDF Slides
  3. Fair Logistic Regression: An Adversarial Perspective Ashkan Rezaei*, Rizal Fathony*, Omid Memarrast, and Brian Ziebart Preprint: arXiv preprint 2019 Link

2018

  1. Distributionally Robust Graphical Models Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang, and Brian Ziebart Conference: Advances in Neural Information Processing Systems (NeurIPS) 2018 Link PDF Poster Code
  2. Consistent Robust Adversarial Prediction for General Multiclass Classification Rizal Fathony, Kaiser Asif, Anqi Liu, Mohammad Ali Bashiri, Wei Xing, Sima Behpour, Xinhua Zhang, and Brian D Ziebart Preprint: arXiv preprint 2018 Link
  3. Learning to Explore by Abstaining Anqi Liu, Rizal Fathony, and Brian Ziebart Workshop: The 13th Women in Machine Learning Workshop (WiML) @ NeurIPS 2018
  4. Efficient and Consistent Adversarial Bipartite Matching Rizal Fathony*, Sima Behpour*, Xinhua Zhang, and Brian Ziebart Conference: International Conference on Machine Learning (ICML) 2018 Link PDF Poster Slides Code

2017

  1. Adversarial Surrogate Losses for Ordinal Regression Rizal Fathony, Mohammad Ali Bashiri, and Brian Ziebart Conference: Advances in Neural Information Processing Systems (NeurIPS) 2017 Link PDF Poster Code
  2. Kernel Robust Bias-Aware Prediction under Covariate Shift Anqi Liu, Rizal Fathony, and Brian D Ziebart Preprint: arXiv preprint 2017 Link

2016

  1. Adversarial Multiclass Classification: A Risk Minimization Perspective Rizal Fathony, Anqi Liu, Kaiser Asif, and Brian Ziebart Conference: Advances in Neural Information Processing Systems (NeurIPS) 2016 Link PDF Poster Code