Rizal Fathony

Orcid: 0000-0003-1538-9090

According to our database1, Rizal Fathony authored at least 16 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs.
Proceedings of the International Joint Conference on Neural Networks, 2024

Partitioning Message Passing for Graph Fraud Detection.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Fairness for Robust Learning to Rank.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs.
Proceedings of the International Joint Conference on Neural Networks, 2023

2022
PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks.
Proceedings of the IEEE International Conference on Knowledge Graph, 2022

2021
Multiplicative Filter Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Fairness for Robust Log Loss Classification.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Fair Logistic Regression: An Adversarial Perspective.
CoRR, 2019

2018
Consistent Robust Adversarial Prediction for General Multiclass Classification.
CoRR, 2018

Distributionally Robust Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Efficient and Consistent Adversarial Bipartite Matching.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Kernel Robust Bias-Aware Prediction under Covariate Shift.
CoRR, 2017

Adversarial Surrogate Losses for Ordinal Regression.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Adversarial Multiclass Classification: A Risk Minimization Perspective.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016


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