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Author

Rizal Fathony

Observed name: Fathony, Rizal
ORCID: 0000-0003-1538-9090
Observed ORCID: 0000-0003-1538-9090
OpenAlex ID: A5005784479
Fairness for Robust Log Loss Classification
2020 · Ashkan Rezaei, Rizal Fathony, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 44
Partitioning Message Passing for Graph Fraud Detection
2024 · Zhuo, Wei, Liu, Zemin, et al. · arXiv (Cornell University) · 31
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Adversarial Surrogate Losses for Ordinal Regression
2017 · Rizal Fathony, Mohammad Bashiri, et al. · neural information processing systems · 20
Adversarial Multiclass Classification: A Risk Minimization Perspective
2016 · Rizal Fathony, Anqi Liu, et al. · neural information processing systems · 13
Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs
2023 · Rizal Fathony, Jenn Ng, et al. · International Joint Conference on Neural Networks (IJCNN) · 12
Fairness for Robust Learning to Rank
2023 · Omid Memarrast, Ashkan Rezaei, et al. · Lecture notes in computer science · 8
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Consistent Robust Adversarial Prediction for General Multiclass Classification
2018 · Fathony, Rizal, Asif, Kaiser, et al. · arXiv (Cornell University) · 8
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Efficient and Consistent Adversarial Bipartite Matching
2018 · Rizal Fathony, Sima Behpour, et al. · International Conference on Machine Learning · 8
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning
2019 · Fathony, Rizal, Kolter, J. Zico · arXiv (Cornell University) · 7
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Distributionally Robust Graphical Models
2018 · Fathony, Rizal, Rezaei, Ashkan, et al. · arXiv (Cornell University) · 6
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Fair Logistic Regression: An Adversarial Perspective.
2019 · Ashkan Rezaei, Rizal Fathony, et al. · arXiv (Cornell University) · 5
The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning
2026 · Agrawal, Aakriti, Chakraborty, Souradip, et al. · arXiv (Cornell University) · 3
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Discrete Wasserstein Generative Adversarial Networks (DWGAN)
2018 · Rizal Fathony, Naveen Goela · 3
Kernel Robust Bias-Aware Prediction under Covariate Shift
2017 · Liu, Anqi, Fathony, Rizal, et al. · arXiv (Cornell University) · 3
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Audited Conformal Prediction for Classification under Unknown Distribution Shift
2026 · Zhou, Yanfei, Fathony, Rizal, et al. · arXiv (Cornell University) · 2
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Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs
2024 · Rizal Fathony, Jenn Ng, et al. · International Joint Conference on Neural Networks (IJCNN) · 2
FINESSE: An Agent-Based Simulator and Benchmark Dataset for Multimodal Financial Event Sequences
2026 · Farnan, Tyler, Eng, Benjamin, et al. · arXiv (Cornell University)
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Multi-Label Node Classification with Label Influence Propagation
2026 · Sun, Yifei, Liu, Zemin, et al. · arXiv (Cornell University)
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When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models
2026 · Zhang, Ding, Zhou, Runtao, et al. · arXiv (Cornell University)
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Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Tasks
2025 · Fathony, Rizal, Melnyk, Igor, et al. · arXiv (Cornell University)
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PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks
2022 · Soji Adeshina, Jian Zhang, et al. · IEEE International Conference on Knowledge Graph (ICKG)
Works count: 22
Citation count: 175
H-index: 8
I10-index: 5
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