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Rizal Fathony
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Conference and Workshop Papers
- 2024
- [c12]Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen:
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision. ICLR 2024 - [c11]Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen:
Partitioning Message Passing for Graph Fraud Detection. ICLR 2024 - 2023
- [c10]Rizal Fathony, Jenn Ng, Jia Chen:
Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs. IJCNN 2023: 1-10 - [c9]Omid Memarrast
, Ashkan Rezaei
, Rizal Fathony
, Brian D. Ziebart
:
Fairness for Robust Learning to Rank. PAKDD (1) 2023: 544-556 - 2022
- [c8]Soji Adeshina, Jian Zhang, Muhyun Kim, Min Chen, Rizal Fathony, Advitiya Vashisht, Jia Chen, George Karypis:
PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks. ICKG 2022: 6-13 - 2021
- [c7]Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter:
Multiplicative Filter Networks. ICLR 2021 - 2020
- [c6]Ashkan Rezaei, Rizal Fathony, Omid Memarrast, Brian D. Ziebart:
Fairness for Robust Log Loss Classification. AAAI 2020: 5511-5518 - [c5]Rizal Fathony, J. Zico Kolter:
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning. AISTATS 2020: 4130-4140 - 2018
- [c4]Rizal Fathony, Sima Behpour, Xinhua Zhang, Brian D. Ziebart:
Efficient and Consistent Adversarial Bipartite Matching. ICML 2018: 1456-1465 - [c3]Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang, Brian D. Ziebart:
Distributionally Robust Graphical Models. NeurIPS 2018: 8354-8365 - 2017
- [c2]Rizal Fathony, Mohammad Ali Bashiri, Brian D. Ziebart:
Adversarial Surrogate Losses for Ordinal Regression. NIPS 2017: 563-573 - 2016
- [c1]Rizal Fathony, Anqi Liu, Kaiser Asif, Brian D. Ziebart:
Adversarial Multiclass Classification: A Risk Minimization Perspective. NIPS 2016: 559-567
Informal and Other Publications
- 2021
- [i6]Omid Memarrast, Ashkan Rezaei, Rizal Fathony, Brian D. Ziebart:
Fairness for Robust Learning to Rank. CoRR abs/2112.06288 (2021) - 2019
- [i5]Ashkan Rezaei, Rizal Fathony, Omid Memarrast, Brian D. Ziebart:
Fair Logistic Regression: An Adversarial Perspective. CoRR abs/1903.03910 (2019) - [i4]Rizal Fathony, J. Zico Kolter:
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning. CoRR abs/1912.00965 (2019) - 2018
- [i3]Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang, Brian D. Ziebart:
Distributionally Robust Graphical Models. CoRR abs/1811.02728 (2018) - [i2]Rizal Fathony, Kaiser Asif, Anqi Liu, Mohammad Ali Bashiri, Wei Xing, Sima Behpour, Xinhua Zhang, Brian D. Ziebart:
Consistent Robust Adversarial Prediction for General Multiclass Classification. CoRR abs/1812.07526 (2018) - 2017
- [i1]Anqi Liu, Rizal Fathony, Brian D. Ziebart:
Kernel Robust Bias-Aware Prediction under Covariate Shift. CoRR abs/1712.10050 (2017)
Coauthor Index
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