Adversarial Multiclass Classification: A Risk Minimization Perspective. - Rizal Fathony; Anqi Liu; Kaiser Asif; Brian D. Ziebart (NIPS, 2016)

Adversarial Surrogate Losses for Ordinal Regression. - Rizal Fathony; Mohammad Ali Bashiri; Brian D. Ziebart (NIPS, 2017)

Kernel Robust Bias-Aware Prediction under Covariate Shift. - Anqi Liu; Rizal Fathony; Brian D. Ziebart (CoRR, 2017)

Efficient and Consistent Adversarial Bipartite Matching. - Rizal Fathony; Sima Behpour; Xinhua Zhang; Brian D. Ziebart (ICML, 2018)

Distributionally Robust Graphical Models. - Rizal Fathony; Ashkan Rezaei; Mohammad Ali Bashiri; Xinhua Zhang; Brian D. Ziebart (NeurIPS, 2018)

Consistent Robust Adversarial Prediction for General Multiclass Classification. - Rizal Fathony; Kaiser Asif; Anqi Liu; Mohammad Ali Bashiri; Wei Xing; Sima Behpour; Xinhua Zhang; Brian D. Ziebart (CoRR, 2018)

Fair Logistic Regression: An Adversarial Perspective. - Ashkan Rezaei; Rizal Fathony; Omid Memarrast; Brian D. Ziebart (CoRR, 2019)

Fairness for Robust Log Loss Classification. - Ashkan Rezaei; Rizal Fathony; Omid Memarrast; Brian D. Ziebart (AAAI, 2020)

AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning. - Rizal Fathony; J. Zico Kolter (AISTATS, 2020)

Multiplicative Filter Networks. - Rizal Fathony; Anit Kumar Sahu; Devin Willmott; J. Zico Kolter (ICLR, 2021)

PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks. - Soji Adeshina; Jian Zhang; Muhyun Kim; Min Chen; Rizal Fathony; Advitiya Vashisht; Jia Chen; George Karypis (ICKG, 2022)

Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs. - Rizal Fathony; Jenn Ng; Jia Chen (IJCNN, 2023)

Fairness for Robust Learning to Rank. - Omid Memarrast; Ashkan Rezaei; Rizal Fathony; Brian D. Ziebart (PAKDD (1), 2023)

Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision. - Nan Chen; Zemin Liu; Bryan Hooi; Bingsheng He; Rizal Fathony; Jun Hu 016; Jia Chen (ICLR, 2024)

Partitioning Message Passing for Graph Fraud Detection. - Wei Zhuo 006; Zemin Liu; Bryan Hooi; Bingsheng He; Guang Tan; Rizal Fathony; Jia Chen (ICLR, 2024)

Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs. - Rizal Fathony; Jenn Ng; Jia Chen (IJCNN, 2024)

Multi-Label Node Classification with Label Influence Propagation. - Yifei Sun 002; Zemin Liu; Bryan Hooi; Yang Yang 009; Rizal Fathony; Jia Chen; Bingsheng He (ICLR, 2025)